提交其余项目实验变更
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# Q2 后续实验协议
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本文件只规定后续实验如何公平比较，不保存已经结束的实验数值或结论。当前维护的参照模型为 **EarlyConcat + BiGRU** 和 **MoFE-7 + MLP Router**。
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## 固定比较条件
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- 使用附件 2 的官方训练/验证划分和 `aligned_50.pkl`。每个样本的 50 个有序词片位置不能描述成 Q1 的 50 个物理时间箱。
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- 两个参照模型和候选模型使用相同输入特征、显式观测掩码、训练集 median/MAD 标准化，以及相同的联合极性分类和强度回归目标。
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- 训练缺失增强与验证缺失都使用连续块。验证条件包括 clean，以及 Text、Audio、Vision、Audio+Vision、All-modal 五种模式在 10%、20%、30% 缺失率下的表现。
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- 默认种子为 42、3407、2026。候选模型必须与两个参照使用相同的划分、种子和验证条件。
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- 分别报告 Accuracy、Macro-F1、MAE、Pearson；同时报告相对 clean 的变化、平均缺失表现、最差条件和跨种子均值/标准差。主对比可按来源视频 ID 做成对 bootstrap。
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- 不合并指标构造手工总分；测试标签不得用于训练、模型选择或超参数选择。
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## 参照资产与新实验目录
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当前保留的模型检查点和训练集标准化参数在 `outputs/mofe_7experts/`。该目录作为只读参照保存；不要把新实验结果写入其中。每一轮实验都使用唯一子目录：
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```text
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outputs/followups/<编号_简短假设>/
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```
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训练入口示例：
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```bash
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uv run python -m q2.train_mofe \
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--phase full --seeds 42 3407 2026 \
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--output-dir outputs/followups/F01_local_repair
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```
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每轮只改变一个主要因素。开始训练前先记录假设、唯一改动、预期指标和停止规则；一次改变多个因素时，要拆成能够分别归因的运行。
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## 增加任务专属 Router 的前置条件
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在训练 dual-router 前，先运行 `uv run python -m q2.task_preference`，用保留的 single-router 检查点评估七个模态子集 expert 对分类 Macro-F1、回归 MAE 和 Pearson 的偏好。某个子集可用时强制使用该 expert；不可用时沿用已训练 router 的可用 expert 路由，并报告覆盖比例。若分类和回归的 expert 排名基本一致，或赢家不具备跨 seed 稳定性，就停止在诊断阶段，不增加第二个 Router。
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若未来数据支持稳定的任务偏好分化，再按单因素顺序评估 dual-router：先比较 shared-expert/shared-BiGRU 主模型与 single-router；再比较参数量匹配的加宽 single-router；之后才评估小型 task adapter 或共享首层的 Router。沿用相同输入特征、mask、训练目标、三 seed 和验证条件，并报告分类及回归指标，不以单一综合分决定升级。当前 forced-expert 诊断没有显示稳定分化，详情见 `outputs/followups/D0_task_preference/task_preference_diagnostic.md`。
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## 每轮记录
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每个实验目录至少保存：
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- `hypothesis.md`：研究问题、单一改动和预期现象；
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- `run_manifest.json`：代码版本、配置、输入特征、划分、种子、设备和检查点来源；
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- `metrics_by_condition.csv`、`summary.csv` 和 `paired_bootstrap.csv`；
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- 对应模型检查点、训练历史，以及解释结果所需的诊断图。
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每轮结束时说明：候选模型是否改善平均缺失表现和最差条件；clean 表现是否下降；收益是否跨种子稳定；增加的参数量与训练成本是否值得。若收益只出现在单一缺失模式，应将它报告为该模式的专门化表现，不据此直接替换整体主模型。
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# Q2/Q3 algorithm selection built on Q1 alignment
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# Q2：缺失模态下的多模态情感识别
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## Decision about reusing Q1
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本目录包含 Q2 的训练代码、环境配置和后续实验约定。当前只维护两种模型：
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The transferable part of Q1 is its explicit time correspondence and observation mask: features from different modalities share ordered positions, missing values are accompanied by masks, and a position can be traced to source time. That interface is useful for both Q2 local-gap handling and Q3 evidence localization.
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1. **EarlyConcat + BiGRU**：将文本、音频、视觉特征和观测掩码拼接后，用双向 GRU 建模有序序列，作为简洁基线。
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2. **MoFE-7 + MLP Router**：根据每个位置可用的模态，在七种模态子集专家之间路由，再用共享 BiGRU 建模序列。
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The exact Q1 B1 extraction cannot be rerun over the 4,850 Attachment 2 training examples. Attachment 2 supplies precomputed aligned and unaligned feature tensors, but not the source audio/video or CTC word-time posteriors for the full training set. Its `aligned_50.pkl` also has 50 wordpiece positions and no Q1 `time_bounds_s`; those positions must not be described as the 50 equal-duration physical-time bins exported by `final/Q1`.
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旧的模型比较报告、指标表和图表已清理。不要从此 README 推断模型优劣；后续结果应放进独立实验目录并在新报告中解释。
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Accordingly, the Q2 experiment uses the official aligned feature set as its shared wordpiece axis, and compares it with a fixed equal-window pooling control made from the official unaligned audio/vision sequences. This is a downstream alignment-utility check, not a claim that B1 was recomputed on Attachment 2. The official train/validation split is retained; test labels are not used.
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## 数据与时序表示
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## Q2 candidates
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训练入口读取项目根目录下 `E题数据/附件2-数据集特征文件/aligned_50.pkl` 的官方训练集和验证集。每个样本包含 50 个有序位置，文本、音频、视觉维度分别为 768、74、35，并带有显式观测掩码。这里的 50 个位置是附件 2 提供的词片位置，**不是 50 个等长物理时间箱**。
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All candidates use identical training examples, train-only median/MAD scaling, joint polarity/intensity objectives, and 15 validation corruptions (three contiguous missing rates by five modality patterns).
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Q1 的对齐方法为 Q2 提供了有序的跨模态输入组织方式；Q2 在此基础上处理连续块缺失，不重新提取或改写 Q1 特征。根目录 `math/` 和 `final/Q1/` 中的内容只作只读参考。
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| Candidate | Fusion rule | What it tests |
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| --- | --- | --- |
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| `concat` | Project each modality, concatenate features and availability flags, then run a bidirectional GRU | Strong, simple early-fusion baseline |
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| `gate` | Learn per-slot modality weights, mask unavailable modalities, then run a bidirectional GRU | Whether explicit reliability-aware fusion handles local gaps |
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| `crossattn` | Apply masked cross-modal attention over the 50 shared slots, then temporal pooling | Whether contextual cross-modal exchange improves robustness |
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标准化参数只从训练集拟合。当前保留的两组模型权重及共享标准化参数位于：
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The report keeps Macro-F1, MAE, and Pearson separate. The default selection is Macro-F1-first across local corruption conditions; MAE and Pearson remain explicit tradeoffs, not terms in a constructed total score. The selected architecture is also trained on fixed-window-resampled features as an alignment control. A separate validation control shifts audio and vision by 1–10 positions to measure sensitivity to cross-modal timing.
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## Q3 explanation selection
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The selected Q2 model is frozen. Integrated Gradients and five-slot grouped occlusion are compared on held-out Attachment 2 validation clips using deletion comprehensiveness, sufficiency, and local rank stability. Attachment 4 has original videos and transcripts, so B1's CTC hard word-time procedure can be applied to those 20 clips to map high-importance wordpiece positions back to seconds. The saved Attachment 4 pickle files do not include `time_bounds_s`; explanations therefore retain both the model slot and the CTC-derived word interval, with alignment quality recorded.
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## Run
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The project environment is managed by `uv` and installs the CUDA 13.0 PyTorch build:
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```bash
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cd deep_learning/Q2
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uv sync
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uv run python -m q2.train_compare
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cd ../Q3
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uv run --project ../Q2 python -m q3.explain_selection
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```text
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outputs/mofe_7experts/
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├── aligned_robust_stats.npz
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└── models/
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├── baselines/concat/seed_{42,3407,2026}/model_best.pt
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└── B5_mofe_mlp/seed_{42,3407,2026}/model_best.pt
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```
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The main outputs are written to `outputs/algorithm_selection/`; plots, CSV metrics, run metadata, and checkpoints stay under this directory. The source data, `math`, and `final/Q1` are read-only inputs.
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## 环境
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本项目使用 `uv` 管理 Python 环境。进入本目录后同步锁定依赖：
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```bash
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uv sync --locked
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```
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## 运行
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先用单个种子执行快速检查。每轮运行使用新的目录，避免覆盖保留的参照权重：
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```bash
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uv run python -m q2.train_mofe \
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--phase smoke --seeds 42 \
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--output-dir outputs/followups/F00_smoke
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```
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完整训练和验证示例：
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```bash
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uv run python -m q2.train_mofe \
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--phase full --seeds 42 3407 2026 \
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--output-dir outputs/followups/F01_local_repair
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```
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完整运行会训练两种模型，并在 clean、Text、Audio、Vision、Audio+Vision、All-modal 条件下评估 10%、20%、30% 连续块缺失；结果、检查点和诊断图写入指定目录。默认输出目录是 `outputs/mofe_7experts/`，日常新实验应显式设置 `--output-dir`，避免覆盖保留的权重和标准化参数。
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## 文件索引
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- `q2/data.py`：官方特征读取、观测掩码、训练集 robust scaling 和连续块缺失。
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- `q2/models.py`：EarlyConcat + BiGRU。
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- `q2/mofe.py`：MoFE-7 专家与 MLP 路由器。
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- `q2/train_mofe.py`：两种保留模型的训练、验证、统计和可视化入口。
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- `q2/task_preference.py`：复用现有 MoFE 权重，比较七个 forced expert 的分类/回归偏好。
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- [ALGORITHM.md](ALGORITHM.md)：两个保留模型的算法说明和最新验证集重评结果。
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- [EXPERIMENT_PROTOCOL.md](EXPERIMENT_PROTOCOL.md)：后续实验的固定比较条件与记录要求。
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- `outputs/followups/README.md`：新实验目录的命名和存放规则。
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Q3 暂不在本目录中开展；待 Q2 后续选型完成后再统一规划。
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## 当前任务偏好诊断
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在训练 dual-router 前，先用现有 MoFE-7 检查了七个 forced expert 在分类 Macro-F1 与回归 MAE/Pearson 上的偏好。三个 seed、15 种缺失条件的排名大体一致，没有看到稳定的分类—回归 expert 分工；因此当前不启动 dual-router，仍以 single-router MoFE-7 为活动参照。详见[诊断报告](outputs/followups/D0_task_preference/task_preference_diagnostic.md)及逐条件数据。
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可用以下命令复现该诊断：
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```bash
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uv run python -m q2.task_preference \
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--seeds 42 3407 2026 \
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--output-dir outputs/followups/D0_task_preference
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```
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# Q2 algorithm selection results
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## Q1 alignment transfer decision
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Q1 B1 aligns BERT word features and audio/vision observations with hard CTC word intervals, projects observed features onto a 0.1-second common grid, exports 50 equal-duration physical-time bins, and keeps observation masks. For Q2, the shared ordered axis and explicit masks transfer directly: a local gap stays a local gap after alignment and can be represented without inventing feature values.
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The exact B1 extraction was not recomputed over Attachment 2. The official 4,850-row feature package contains precomputed aligned and unaligned tensors, but no full-set source audio/video or word-time posterior. Its `aligned_50.pkl` has 50 wordpiece positions and no per-slot `time_bounds_s`; those positions are not Q1's 50 equal-duration bins. This experiment therefore trains on the official aligned features and compares them with an equal-window audio/vision resampling control. The comparison tests the value of an aligned ordered representation for the downstream Q2 task; it does not claim to reproduce B1 on all 4,850 clips.
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## Data and protocol
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- Attachment 2 official split: 3,395 training clips and 728 validation clips. Their source-video ID sets do not overlap.
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- Each official aligned example has 50 positions with Text 768-D, Audio 74-D, Vision 35-D features and modality observation masks.
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- Attachment 2 test labels were not used.
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- The three candidates shared train-only median/MAD normalization, the joint polarity/intensity objective, and training-time contiguous block masking.
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- Validation corruption covered 10%, 20%, and 30% of 50 positions for Text, Audio, Vision, Audio+Vision, and all three modalities. This is a wordpiece-position proxy for a continuous time gap; full-set second-level timestamps are not supplied.
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- Each candidate was run with seeds 42, 3407, and 2026. Reported `±` values are seed standard deviations over the fixed official validation set and deterministic corruption draws; they are not confidence intervals over new videos.
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## Fusion comparison
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| Model | Clean Accuracy | Clean Macro-F1 | Corrupt Accuracy, mean | Corrupt Macro-F1, mean | Worst condition Macro-F1 | Corrupt MAE | Corrupt Pearson |
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| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
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| Early concatenation + BiGRU | 0.626 ± 0.013 | 0.580 ± 0.018 | 0.623 ± 0.011 | **0.575 ± 0.017** | **0.516** | **0.640 ± 0.004** | 0.607 ± 0.004 |
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| Reliability gate + BiGRU | 0.621 ± 0.011 | 0.570 ± 0.019 | 0.617 ± 0.011 | 0.565 ± 0.018 | 0.498 | 0.643 ± 0.008 | **0.610 ± 0.008** |
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| Masked cross-modal attention | 0.604 ± 0.012 | 0.540 ± 0.049 | 0.601 ± 0.009 | 0.539 ± 0.047 | 0.462 | 0.649 ± 0.024 | 0.592 ± 0.016 |
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Early concatenation has the best mean corrupted Macro-F1 and MAE. The gate has slightly higher Pearson, so the metrics do not collapse to one score. Cross-modal attention is lower and more variable at this sample size. It is not selected for the next Q2 stage.
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For the selected concatenation model, the hardest tested case is 30% Text masking: Macro-F1 0.547 and MAE 0.665, compared with clean Macro-F1 0.580 and MAE 0.636. Audio-only or Vision-only masking has a smaller effect in these runs. This is evidence about this feature set and these simulated spans; it does not establish a universal modality ranking.
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## Alignment utility control
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The same concatenation model was trained either on the supplied aligned wordpiece features or on equal-window-resampled audio/vision features from the official unaligned tensors.
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| Representation | Clean Macro-F1 | Corrupt Macro-F1 | Corrupt MAE | Corrupt Pearson |
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| --- | ---: | ---: | ---: | ---: |
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| Supplied word-aligned 50 positions | 0.580 ± 0.018 | **0.575 ± 0.017** | **0.640 ± 0.004** | **0.607 ± 0.004** |
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| Equal-window resampled unaligned input | 0.501 ± 0.014 | 0.504 ± 0.016 | 0.665 ± 0.005 | 0.577 ± 0.010 |
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On the selected model, shifting Audio and Vision by 1–10 positions changed aligned Macro-F1 from 0.580 to 0.557. That is a modest timing-sensitivity signal; it does not prove the model uses precise physical-time correspondence. Together with the fixed-window comparison, the result supports retaining the supplied aligned sequence for Q2.
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## Selected Q2 direction
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Continue with mask-aware early concatenation plus a bidirectional GRU, using local block masking during training. Keep the reliability gate as an ablation because its Pearson is slightly higher. Revisit cross-attention only if a later run has stronger evidence and enough data to control overfitting.
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## Reproducible artifacts
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- [Model and representation summary](outputs/algorithm_selection/summary.csv)
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- [Metrics by missing type and rate](outputs/algorithm_selection/validation_metrics_by_condition.csv)
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- [Aligned versus fixed-window and temporal-shift controls](outputs/algorithm_selection/alignment_transfer_ablation.csv)
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- [Training/data audit and run manifest](outputs/algorithm_selection/data_audit.json), [run manifest](outputs/algorithm_selection/run_manifest.json)
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- [Validation plot](outputs/algorithm_selection/missing_rate_comparison.png)
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- [Selected seed-42 checkpoint](outputs/algorithm_selection/models/aligned/concat/model_best.pt)
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The fitted checkpoint is for algorithm selection, not the final Attachment 3 submission model. The final model should be trained on train+validation after the architecture and thresholds are frozen.
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@@ -1,7 +0,0 @@
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method,representation,condition,n_valid,n_seeds,accuracy,accuracy_sd,macro_f1,macro_f1_sd,mae,mae_sd,pearson,pearson_sd,missing_rate
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concat,provided_word_aligned_50,clean,728,3,0.6259157509157509,0.012689016905266455,0.5803030257575642,0.01849482950112713,0.6362011035283407,0.0035474183737517766,0.6131094378711319,0.003049322677391937,
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concat,provided_word_aligned_50,audio_vision_shifted_1_to_10_slots,728,3,0.6144688644688645,0.017174907814570563,0.5566710058858901,0.02417454695632849,0.6264231006304423,0.003071737263575265,0.610966440919508,0.00045089311901344093,
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concat,provided_word_aligned_50,all_local_corruption_mean,728,3,0.6226800976800977,0.011084117339613314,0.5751264735191365,0.016846851540436875,0.6402280900213454,0.004374268275822229,0.6068152054284395,0.004485336212715804,0.20000000000000004
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concat,equal_window_resampled_unaligned,clean,728,3,0.586996336996337,0.010491244722884272,0.5005019574320758,0.013925639871727626,0.6615431904792786,0.005397772426619935,0.581966026863303,0.009642037378255953,
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concat,equal_window_resampled_unaligned,audio_vision_shifted_1_to_10_slots,728,3,0.5956959706959707,0.010309826235528995,0.5144238712048543,0.010932166832616294,0.6616438627243042,0.005509720037298075,0.5807893064362651,0.010274359593119802,
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concat,equal_window_resampled_unaligned,all_local_corruption_mean,728,3,0.5905677655677655,0.006480515023060099,0.5042920441199125,0.015580461355158729,0.6651763810051813,0.004962154081458186,0.5766306314815771,0.010310184996660417,0.20000000000000004
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|
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{
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"source": "/home/gloamxun/modeling_zhaocui/E题数据/附件2-数据集特征文件/aligned_50.pkl",
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"train_samples": 3395,
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"valid_samples": 728,
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"train_classes": [
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967,
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758,
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1670
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],
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"valid_classes": [
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206,
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184,
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338
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],
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"mean_observed_slots": {
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"text": 24.645655375552284,
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"audio": 22.626509572901327,
|
||||
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{
|
||||
"source_feature": "/home/gloamxun/modeling_zhaocui/E题数据/附件2-数据集特征文件/aligned_50.pkl",
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||||
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||||
42,
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3407,
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||||
2026
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||||
},
|
||||
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|
||||
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|
||||
"models": [
|
||||
"concat",
|
||||
"gate",
|
||||
"crossattn"
|
||||
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|
||||
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|
||||
0.1,
|
||||
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|
||||
0.3
|
||||
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|
||||
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|
||||
"text",
|
||||
"audio",
|
||||
"vision",
|
||||
"audio_vision",
|
||||
"all_modalities"
|
||||
],
|
||||
"feature_scaling": "training split median/MAD; fallback to standard deviation for zero-MAD dimensions",
|
||||
"test_labels_used": false,
|
||||
"alignment_transfer_limit": "The official aligned_50 data use a 50-slot wordpiece sequence with no per-slot seconds or stored Q1 B1 time_bounds. The fixed-window comparison is a downstream alignment control, not a re-run of Q1 B1 on the full dataset.",
|
||||
"python": "3.14.7 (main, Aug 10 2026, 00:00:00) [GCC 16.1.1 20260515 (Red Hat 16.1.1-2)]",
|
||||
"torch": "2.14.0+cu130",
|
||||
"numpy": "2.5.3",
|
||||
"created_unix": 1790237371.5417986
|
||||
}
|
||||
@@ -1 +0,0 @@
|
||||
Macro-F1-first validation selection: concat. See summary.csv for the full multi-metric tradeoff.
|
||||
@@ -1,5 +0,0 @@
|
||||
method,representation,n_seeds,clean_accuracy,clean_accuracy_sd,clean_macro_f1,clean_macro_f1_sd,clean_mae,clean_mae_sd,clean_pearson,clean_pearson_sd,corrupt_accuracy_mean,corrupt_accuracy_sd,corrupt_macro_f1_mean,corrupt_macro_f1_sd,corrupt_macro_f1_worst,corrupt_mae_mean,corrupt_mae_sd,corrupt_pearson_mean,corrupt_pearson_sd,f1_rate_10,accuracy_rate_10,mae_rate_10,f1_rate_20,accuracy_rate_20,mae_rate_20,f1_rate_30,accuracy_rate_30,mae_rate_30,pareto_nondominated
|
||||
concat,provided_word_aligned_50,3,0.6259157509157509,0.012689016905266455,0.5803030257575643,0.01849482950112713,0.6362011035283407,0.0035474183737517766,0.6131094378711319,0.003049322677391937,0.6226800976800976,0.011084117339613314,0.5751264735191365,0.016846851540436875,0.5160231153138954,0.6402280900213454,0.004374268275822229,0.6068152054284395,0.004485336212715804,0.5774116129988989,0.6244505494505495,0.6361218094825745,0.5732483562656322,0.6214285714285714,0.6398131450017294,0.5747194512928783,0.6221611721611722,0.6447493155797323,True
|
||||
gate,provided_word_aligned_50,3,0.6213369963369964,0.0106695789356511,0.570042406396691,0.0192417246427628,0.6392609675725301,0.010298306434114075,0.61843647657748,0.008153726338115605,0.6170940170940171,0.011429412792673272,0.5654484786987964,0.018209275544794713,0.4977788775985414,0.6432029167811076,0.00818900735475074,0.6097108251803484,0.008038674969140262,0.5690117947676202,0.6205128205128205,0.6386720657348633,0.5668714434894636,0.6183150183150183,0.6423242449760437,0.5604621978393048,0.6124542124542125,0.6486124396324157,True
|
||||
crossattn,provided_word_aligned_50,3,0.6039377289377289,0.011682555697960702,0.5402080959251137,0.04931996722297363,0.6486262281735738,0.0247913008377115,0.5962298100136721,0.016314693282960167,0.6013125763125764,0.00904432495782142,0.5394035484113701,0.047085193081398864,0.4615384615384615,0.6492320696512858,0.023553864046032207,0.5917838426035978,0.015944508668008214,0.5437388259395578,0.6055860805860807,0.6467597643534342,0.5379114650369052,0.5998168498168498,0.6491282820701599,0.5365603542576471,0.5985347985347985,0.6518081625302632,False
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crossattn,provided_word_aligned_50,3407,text,0.1,728,0.6112637362637363,0.5835380749854434,0.6310563683509827,0.599629174971605
|
||||
crossattn,provided_word_aligned_50,3407,audio,0.1,728,0.6222527472527473,0.5972489054492567,0.623246431350708,0.6125511992350159
|
||||
crossattn,provided_word_aligned_50,3407,vision,0.1,728,0.6098901098901099,0.583342725650418,0.6262677311897278,0.6099948694514816
|
||||
crossattn,provided_word_aligned_50,3407,audio_vision,0.1,728,0.6112637362637363,0.5867178901767943,0.623745322227478,0.6093859569553041
|
||||
crossattn,provided_word_aligned_50,3407,all_modalities,0.1,728,0.614010989010989,0.5888196778236806,0.6245514750480652,0.6117287980833325
|
||||
crossattn,provided_word_aligned_50,3407,text,0.2,728,0.6043956043956044,0.5717745964093709,0.6391856074333191,0.5848733951460722
|
||||
crossattn,provided_word_aligned_50,3407,audio,0.2,728,0.6112637362637363,0.5894389643701733,0.6257225871086121,0.6074896792266403
|
||||
crossattn,provided_word_aligned_50,3407,vision,0.2,728,0.6112637362637363,0.5851332896742695,0.6264434456825256,0.6127778365291627
|
||||
crossattn,provided_word_aligned_50,3407,audio_vision,0.2,728,0.614010989010989,0.5949110192264351,0.6187586188316345,0.6182033017472267
|
||||
crossattn,provided_word_aligned_50,3407,all_modalities,0.2,728,0.6016483516483516,0.5773507156134905,0.634911835193634,0.592528289751998
|
||||
crossattn,provided_word_aligned_50,3407,text,0.3,728,0.6002747252747253,0.5711675869572423,0.6530678868293762,0.5606507699299987
|
||||
crossattn,provided_word_aligned_50,3407,audio,0.3,728,0.614010989010989,0.5913067138879948,0.6232653856277466,0.608846448174426
|
||||
crossattn,provided_word_aligned_50,3407,vision,0.3,728,0.6071428571428571,0.5819589420485362,0.6271139979362488,0.6113427502800617
|
||||
crossattn,provided_word_aligned_50,3407,audio_vision,0.3,728,0.6098901098901099,0.5897044167286073,0.6164263486862183,0.6193569599948916
|
||||
crossattn,provided_word_aligned_50,3407,all_modalities,0.3,728,0.6181318681318682,0.5940082804540815,0.6317148804664612,0.5948538231621964
|
||||
crossattn,provided_word_aligned_50,2026,clean,0.0,728,0.592032967032967,0.5420592129348364,0.6422320604324341,0.6024037597271933
|
||||
crossattn,provided_word_aligned_50,2026,text,0.1,728,0.5975274725274725,0.5454707818440054,0.6418640613555908,0.6024112136660502
|
||||
crossattn,provided_word_aligned_50,2026,audio,0.1,728,0.5934065934065934,0.5436021768815864,0.6399821043014526,0.6049551097626092
|
||||
crossattn,provided_word_aligned_50,2026,vision,0.1,728,0.5892857142857143,0.5384039205789096,0.6415307521820068,0.6011185044495995
|
||||
crossattn,provided_word_aligned_50,2026,audio_vision,0.1,728,0.603021978021978,0.554150981347194,0.6382296681404114,0.6055650886270252
|
||||
crossattn,provided_word_aligned_50,2026,all_modalities,0.1,728,0.6002747252747253,0.5487055723716843,0.6430385112762451,0.5965045050053945
|
||||
crossattn,provided_word_aligned_50,2026,text,0.2,728,0.5906593406593407,0.5288690186841035,0.6494663953781128,0.5950657404432197
|
||||
crossattn,provided_word_aligned_50,2026,audio,0.2,728,0.5906593406593407,0.5424377950535354,0.6427614688873291,0.601656698677867
|
||||
crossattn,provided_word_aligned_50,2026,vision,0.2,728,0.5934065934065934,0.5455594737723953,0.6451690793037415,0.5999133532386576
|
||||
crossattn,provided_word_aligned_50,2026,audio_vision,0.2,728,0.5961538461538461,0.5478165327681003,0.6367671489715576,0.6098925146891432
|
||||
crossattn,provided_word_aligned_50,2026,all_modalities,0.2,728,0.5892857142857143,0.5359341358069671,0.6405748724937439,0.5950458235969649
|
||||
crossattn,provided_word_aligned_50,2026,text,0.3,728,0.5755494505494505,0.5101004599189818,0.6680996417999268,0.565804882523542
|
||||
crossattn,provided_word_aligned_50,2026,audio,0.3,728,0.603021978021978,0.5546585571147281,0.6443181037902832,0.6002440646348579
|
||||
crossattn,provided_word_aligned_50,2026,vision,0.3,728,0.5989010989010989,0.5523658108429751,0.6397479772567749,0.6069549742183601
|
||||
crossattn,provided_word_aligned_50,2026,audio_vision,0.3,728,0.5879120879120879,0.5420598732858583,0.6358648538589478,0.6059215495922518
|
||||
crossattn,provided_word_aligned_50,2026,all_modalities,0.3,728,0.5810439560439561,0.5222533299835609,0.6609663367271423,0.5802332350553648
|
||||
concat,provided_word_aligned_50,42,audio_vision_shifted_1_to_10_slots,0.0,728,0.6222527472527473,0.5650157195157686,0.6228974461555481,0.6112627581844078
|
||||
concat,provided_word_aligned_50,3407,audio_vision_shifted_1_to_10_slots,0.0,728,0.6263736263736264,0.5755677417356012,0.6278499364852905,0.6111890270289838
|
||||
concat,provided_word_aligned_50,2026,audio_vision_shifted_1_to_10_slots,0.0,728,0.5947802197802198,0.5294295564063006,0.6285219192504883,0.6104475375451327
|
||||
concat,equal_window_resampled_unaligned,42,clean,0.0,728,0.5892857142857143,0.4853955760688928,0.6553117632865906,0.587849225352828
|
||||
concat,equal_window_resampled_unaligned,42,text,0.1,728,0.5892857142857143,0.48234450535531,0.6542671918869019,0.5821794113270566
|
||||
concat,equal_window_resampled_unaligned,42,audio,0.1,728,0.5879120879120879,0.4840888292569874,0.6544017195701599,0.589859444837917
|
||||
concat,equal_window_resampled_unaligned,42,vision,0.1,728,0.5906593406593407,0.48684880290869176,0.6560104489326477,0.5873086725722289
|
||||
concat,equal_window_resampled_unaligned,42,audio_vision,0.1,728,0.5961538461538461,0.49502890457555865,0.6592482924461365,0.5895610005108267
|
||||
concat,equal_window_resampled_unaligned,42,all_modalities,0.1,728,0.5865384615384616,0.4839129480007753,0.661249577999115,0.5814457099031457
|
||||
concat,equal_window_resampled_unaligned,42,text,0.2,728,0.5741758241758241,0.4641572706698656,0.6567733883857727,0.5645263734507251
|
||||
concat,equal_window_resampled_unaligned,42,audio,0.2,728,0.5934065934065934,0.49411312080823294,0.6519993543624878,0.5919285095409706
|
||||
concat,equal_window_resampled_unaligned,42,vision,0.2,728,0.5851648351648352,0.4807564908587733,0.6555609107017517,0.5864882167667788
|
||||
concat,equal_window_resampled_unaligned,42,audio_vision,0.2,728,0.5947802197802198,0.486680557422301,0.6588707566261292,0.5950950548477731
|
||||
concat,equal_window_resampled_unaligned,42,all_modalities,0.2,728,0.5824175824175825,0.4826855628872202,0.6649248003959656,0.5778664904235934
|
||||
concat,equal_window_resampled_unaligned,42,text,0.3,728,0.5769230769230769,0.47568745986340694,0.6655409932136536,0.5549458556193816
|
||||
concat,equal_window_resampled_unaligned,42,audio,0.3,728,0.5865384615384616,0.49062463717636134,0.6570892930030823,0.5903076532449915
|
||||
concat,equal_window_resampled_unaligned,42,vision,0.3,728,0.5934065934065934,0.49023200117754157,0.6581456661224365,0.5844521656955831
|
||||
concat,equal_window_resampled_unaligned,42,audio_vision,0.3,728,0.6057692307692307,0.5036551721604455,0.6700985431671143,0.5948534685103303
|
||||
concat,equal_window_resampled_unaligned,42,all_modalities,0.3,728,0.5989010989010989,0.49385933420149347,0.6675514578819275,0.5765029580102057
|
||||
concat,equal_window_resampled_unaligned,42,audio_vision_shifted_1_to_10_slots,0.0,728,0.5961538461538461,0.5023963012985687,0.6553080081939697,0.5869747480356168
|
||||
concat,equal_window_resampled_unaligned,3407,clean,0.0,728,0.5961538461538461,0.512827084557042,0.664772629737854,0.5872103830577866
|
||||
concat,equal_window_resampled_unaligned,3407,text,0.1,728,0.6002747252747253,0.5143254275091239,0.6675248146057129,0.5790469117683982
|
||||
concat,equal_window_resampled_unaligned,3407,audio,0.1,728,0.5961538461538461,0.5141876873569328,0.6630795001983643,0.5887049023755868
|
||||
concat,equal_window_resampled_unaligned,3407,vision,0.1,728,0.592032967032967,0.5021484550452703,0.6637163758277893,0.588692970574274
|
||||
concat,equal_window_resampled_unaligned,3407,audio_vision,0.1,728,0.6002747252747253,0.5172277536075813,0.6633241176605225,0.592489640322385
|
||||
concat,equal_window_resampled_unaligned,3407,all_modalities,0.1,728,0.6043956043956044,0.5264327838402229,0.6659616231918335,0.5874171690472151
|
||||
concat,equal_window_resampled_unaligned,3407,text,0.2,728,0.5810439560439561,0.49649824913662327,0.6659781336784363,0.5747007869349695
|
||||
concat,equal_window_resampled_unaligned,3407,audio,0.2,728,0.6002747252747253,0.5210696576225557,0.662110447883606,0.5898815380715464
|
||||
concat,equal_window_resampled_unaligned,3407,vision,0.2,728,0.603021978021978,0.5134655842561412,0.6635054349899292,0.5874898942649338
|
||||
concat,equal_window_resampled_unaligned,3407,audio_vision,0.2,728,0.6043956043956044,0.5213539297376665,0.665846586227417,0.591038037009385
|
||||
concat,equal_window_resampled_unaligned,3407,all_modalities,0.2,728,0.592032967032967,0.5111232435941855,0.6659784317016602,0.5810186064947893
|
||||
concat,equal_window_resampled_unaligned,3407,text,0.3,728,0.5824175824175825,0.49292032420488613,0.6802199482917786,0.5488280644778166
|
||||
concat,equal_window_resampled_unaligned,3407,audio,0.3,728,0.603021978021978,0.5278870449050491,0.6631943583488464,0.587517131217198
|
||||
concat,equal_window_resampled_unaligned,3407,vision,0.3,728,0.6043956043956044,0.5144897492123951,0.6652408838272095,0.5849148208986014
|
||||
concat,equal_window_resampled_unaligned,3407,audio_vision,0.3,728,0.6057692307692307,0.5222120983952546,0.6709288954734802,0.5894788895188137
|
||||
concat,equal_window_resampled_unaligned,3407,all_modalities,0.3,728,0.5934065934065934,0.5118478541545217,0.6919083595275879,0.558672500491863
|
||||
concat,equal_window_resampled_unaligned,3407,audio_vision_shifted_1_to_10_slots,0.0,728,0.6057692307692307,0.5237566082920623,0.6653115153312683,0.5864640082461416
|
||||
concat,equal_window_resampled_unaligned,2026,clean,0.0,728,0.5755494505494505,0.5032832116702929,0.6645451784133911,0.5708384721792944
|
||||
concat,equal_window_resampled_unaligned,2026,text,0.1,728,0.5686813186813187,0.4953554567971044,0.6647433638572693,0.5624346756639816
|
||||
concat,equal_window_resampled_unaligned,2026,audio,0.1,728,0.592032967032967,0.524084368831769,0.6619700789451599,0.5727849021508449
|
||||
concat,equal_window_resampled_unaligned,2026,vision,0.1,728,0.5837912087912088,0.5121488634353761,0.6646548509597778,0.5731723699341335
|
||||
concat,equal_window_resampled_unaligned,2026,audio_vision,0.1,728,0.5879120879120879,0.5138457090126345,0.6634346842765808,0.5783368477304374
|
||||
concat,equal_window_resampled_unaligned,2026,all_modalities,0.1,728,0.5837912087912088,0.5112311206228025,0.6690692901611328,0.5634143872695312
|
||||
concat,equal_window_resampled_unaligned,2026,text,0.2,728,0.570054945054945,0.4938343318957674,0.6707639694213867,0.5459273537200591
|
||||
concat,equal_window_resampled_unaligned,2026,audio,0.2,728,0.5934065934065934,0.5230327607731714,0.6592981815338135,0.5755735913907287
|
||||
concat,equal_window_resampled_unaligned,2026,vision,0.2,728,0.5906593406593407,0.5211672989417647,0.6658343076705933,0.5720666083948681
|
||||
concat,equal_window_resampled_unaligned,2026,audio_vision,0.2,728,0.5989010989010989,0.5276783237584716,0.6637739539146423,0.583433626473117
|
||||
concat,equal_window_resampled_unaligned,2026,all_modalities,0.2,728,0.5851648351648352,0.5131525873114892,0.6693573594093323,0.5605391525623993
|
||||
concat,equal_window_resampled_unaligned,2026,text,0.3,728,0.5508241758241759,0.4775661528696233,0.6854801177978516,0.5184409269913169
|
||||
concat,equal_window_resampled_unaligned,2026,audio,0.3,728,0.5989010989010989,0.5333065606332371,0.6566126942634583,0.576381050540554
|
||||
concat,equal_window_resampled_unaligned,2026,vision,0.3,728,0.592032967032967,0.5197981617020956,0.6703022122383118,0.5691319241770694
|
||||
concat,equal_window_resampled_unaligned,2026,audio_vision,0.3,728,0.6016483516483516,0.5344217204682321,0.6686394214630127,0.5850381809653504
|
||||
concat,equal_window_resampled_unaligned,2026,all_modalities,0.3,728,0.5728021978021978,0.4906531284411469,0.6887523531913757,0.5344899699772931
|
||||
concat,equal_window_resampled_unaligned,2026,audio_vision_shifted_1_to_10_slots,0.0,728,0.5851648351648352,0.5171187040239319,0.6643120646476746,0.5689291630270369
|
||||
|
+9
@@ -0,0 +1,9 @@
|
||||
expert,n_seeds,conditions_averaged,corrupt_macro_f1_mean,corrupt_macro_f1_seed_sd,corrupt_mae_mean,corrupt_mae_seed_sd,corrupt_pearson_mean,corrupt_pearson_seed_sd,corrupt_available_position_fraction_mean,corrupt_available_position_fraction_seed_sd
|
||||
T,3,15,0.589757307588876,0.0020352263518919928,0.6427479929394192,0.011099141735671992,0.6055934960695915,0.011249087713636004,0.4713144275877211,0.0009020844190840855
|
||||
A,3,15,0.31808865690767957,0.021317873724056042,0.7786133103900484,0.02215640639085551,0.2517374183437017,0.056858036666330804,0.41234615974956085,0.0006123395125548464
|
||||
V,3,15,0.4294686868255882,0.00702363166013299,0.746937084197998,0.018509741647116298,0.3397204968144785,0.03755825627467872,0.38980709380573697,0.0007666997275958537
|
||||
TA,3,15,0.5669756392100714,0.01133309602845077,0.6594201882680256,0.01470301824398307,0.5769403121670593,0.018611300259088026,0.39344567192925345,0.001209217023352635
|
||||
TV,3,15,0.5614920808228451,0.019711265507630443,0.6670825415187411,0.023795316023615953,0.567084624145485,0.0207702286048309,0.3718882878621419,0.0013093468654614014
|
||||
AV,3,15,0.39277649494622896,0.020026357257377843,0.7993785394562615,0.035564809067982435,0.34948917366719146,0.02272610332661933,0.37169109582901,0.0008765253565872557
|
||||
TAV,3,15,0.5310708763875678,0.04085138769461332,0.7081663846969605,0.04967350356763789,0.5417887241832338,0.025764587032271177,0.353772289885415,0.0014139247968273899
|
||||
learned_router,3,15,0.5996814814915562,0.009482724136440013,0.6405956612692939,0.01886112793147847,0.6049016689353811,0.007374661467605528,0.4902148962148963,0.00031441255612441293
|
||||
|
@@ -0,0 +1,385 @@
|
||||
method,seed,condition,missing_rate,expert,n_valid,available_position_fraction,accuracy,macro_f1,mae,pearson
|
||||
B5_mofe_mlp,42,clean,0.0,learned_router,728,0.5117582417582418,0.6538461538461539,0.6219292861291515,0.6228764653205872,0.6143991681634768
|
||||
B5_mofe_mlp,42,clean,0.0,T,728,0.5117582678794861,0.6304945054945055,0.595530036337148,0.6439221501350403,0.6129421272609571
|
||||
B5_mofe_mlp,42,clean,0.0,A,728,0.47049450874328613,0.47527472527472525,0.298145070470697,0.7733861207962036,0.18784970953005917
|
||||
B5_mofe_mlp,42,clean,0.0,V,728,0.44483518600463867,0.5027472527472527,0.40175895555984303,0.766243577003479,0.24655662252226374
|
||||
B5_mofe_mlp,42,clean,0.0,TA,728,0.47049450874328613,0.6126373626373627,0.5778441259738553,0.6754669547080994,0.5976612786856457
|
||||
B5_mofe_mlp,42,clean,0.0,TV,728,0.44483518600463867,0.5659340659340659,0.5313464424314036,0.6711714267730713,0.5439696393509325
|
||||
B5_mofe_mlp,42,clean,0.0,AV,728,0.44483518600463867,0.39972527472527475,0.32010564554339865,0.8058619499206543,0.28534741724537543
|
||||
B5_mofe_mlp,42,clean,0.0,TAV,728,0.44483518600463867,0.5192307692307693,0.5075932022075595,0.7201082110404968,0.5295943406640352
|
||||
B5_mofe_mlp,42,text_10,0.1,learned_router,728,0.5092032967032967,0.6497252747252747,0.6156314005702952,0.6238095760345459,0.6073313719228126
|
||||
B5_mofe_mlp,42,text_10,0.1,T,728,0.46244505047798157,0.625,0.586687579750888,0.6396907567977905,0.6069353813986993
|
||||
B5_mofe_mlp,42,text_10,0.1,A,728,0.47049450874328613,0.4725274725274725,0.29847247595086945,0.7734847068786621,0.1872762163407035
|
||||
B5_mofe_mlp,42,text_10,0.1,V,728,0.44483518600463867,0.5013736263736264,0.40093402112196824,0.7681401968002319,0.23859035367845496
|
||||
B5_mofe_mlp,42,text_10,0.1,TA,728,0.4237362742424011,0.6043956043956044,0.5640906610207688,0.6682834029197693,0.5903746167194355
|
||||
B5_mofe_mlp,42,text_10,0.1,TV,728,0.40118134021759033,0.5590659340659341,0.5191159133025295,0.6736815571784973,0.5364920078295683
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||||
B5_mofe_mlp,42,text_10,0.1,AV,728,0.44483518600463867,0.39697802197802196,0.31798635878496145,0.8078023195266724,0.280227031807917
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||||
B5_mofe_mlp,42,text_10,0.1,TAV,728,0.40118134021759033,0.5233516483516484,0.5067270736643431,0.7274371385574341,0.5169177462509623
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||||
B5_mofe_mlp,42,audio_10,0.1,learned_router,728,0.5117582417582418,0.6497252747252747,0.6192151480683822,0.6202160716056824,0.6147259952822673
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||||
B5_mofe_mlp,42,audio_10,0.1,T,728,0.5117582678794861,0.6291208791208791,0.5945275158931668,0.6429776549339294,0.6132756084561103
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||||
B5_mofe_mlp,42,audio_10,0.1,A,728,0.42186814546585083,0.5206043956043956,0.3800213409408812,0.7459056973457336,0.34520880073060467
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||||
B5_mofe_mlp,42,audio_10,0.1,V,728,0.44483518600463867,0.5027472527472527,0.40304222030887615,0.7655854225158691,0.2472653367702658
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||||
B5_mofe_mlp,42,audio_10,0.1,TA,728,0.42186814546585083,0.6208791208791209,0.5887443905119517,0.6653785705566406,0.6021204010545738
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||||
B5_mofe_mlp,42,audio_10,0.1,TV,728,0.44483518600463867,0.5645604395604396,0.5312885900336469,0.6704310178756714,0.5439517824131759
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||||
B5_mofe_mlp,42,audio_10,0.1,AV,728,0.3990384638309479,0.4642857142857143,0.3849597770559165,0.7626285552978516,0.3957500275879042
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||||
B5_mofe_mlp,42,audio_10,0.1,TAV,728,0.3990384638309479,0.5343406593406593,0.5227392208880216,0.6968366503715515,0.5554522305845234
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||||
B5_mofe_mlp,42,vision_10,0.1,learned_router,728,0.5117582417582418,0.6497252747252747,0.617790322593887,0.6200696229934692,0.6170344442601211
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||||
B5_mofe_mlp,42,vision_10,0.1,T,728,0.5117582678794861,0.6291208791208791,0.5943509173547352,0.644621729850769,0.6129819496927139
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||||
B5_mofe_mlp,42,vision_10,0.1,A,728,0.47049450874328613,0.4766483516483517,0.2989428209119208,0.7728793621063232,0.1876997393849426
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||||
B5_mofe_mlp,42,vision_10,0.1,V,728,0.3976648449897766,0.521978021978022,0.43087711258901057,0.7396351099014282,0.3554676006672735
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||||
B5_mofe_mlp,42,vision_10,0.1,TA,728,0.47049450874328613,0.6098901098901099,0.5742147768264858,0.6766068339347839,0.5972162162499693
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||||
B5_mofe_mlp,42,vision_10,0.1,TV,728,0.3976648449897766,0.5865384615384616,0.55296383612865,0.6538857817649841,0.5634816451275405
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||||
B5_mofe_mlp,42,vision_10,0.1,AV,728,0.3976648449897766,0.4697802197802198,0.3822322738135533,0.7551642656326294,0.38427666063984023
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||||
B5_mofe_mlp,42,vision_10,0.1,TAV,728,0.3976648449897766,0.5494505494505495,0.5360678828855083,0.6838967800140381,0.5509729751679995
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,learned_router,728,0.5117582417582418,0.6524725274725275,0.6211709858768683,0.620396614074707,0.6150188131976286
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,T,728,0.5117582678794861,0.6304945054945055,0.5962642544403453,0.6440324783325195,0.6128135963865373
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,A,728,0.42197802662849426,0.5123626373626373,0.3684800611034152,0.7456803917884827,0.33199125335675117
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,V,728,0.39917582273483276,0.5288461538461539,0.4393232991026214,0.7295647859573364,0.3589534058253107
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,TA,728,0.42197802662849426,0.6071428571428571,0.5708085735541816,0.6724270582199097,0.6024972861010555
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,TV,728,0.39917582273483276,0.5824175824175825,0.5450890570908877,0.6524452567100525,0.5628685312944325
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,AV,728,0.39917582273483276,0.4807692307692308,0.3902098705265415,0.7563263773918152,0.3809815404834876
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||||
B5_mofe_mlp,42,audio_vision_10,0.1,TAV,728,0.39917582273483276,0.5508241758241759,0.5380789099976825,0.6938035488128662,0.5469243453503756
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,learned_router,728,0.4626098901098901,0.6414835164835165,0.6107226107226107,0.6245603561401367,0.6099878332655955
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,T,728,0.4626098871231079,0.6236263736263736,0.5896180574655738,0.644334077835083,0.6061672135521097
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,A,728,0.42359891533851624,0.47802197802197804,0.29851508448322833,0.7703589200973511,0.19932722734527986
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,V,728,0.401016503572464,0.5096153846153846,0.40743192506208387,0.7642088532447815,0.2536262411288443
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,TA,728,0.42359891533851624,0.6071428571428571,0.5695040612711005,0.6758896708488464,0.5936467906721097
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,TV,728,0.401016503572464,0.5769230769230769,0.5415381488196198,0.672159731388092,0.5447658722890104
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,AV,728,0.401016503572464,0.4024725274725275,0.3202895136648401,0.8006964921951294,0.28858272134328355
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||||
B5_mofe_mlp,42,all_modalities_10,0.1,TAV,728,0.401016503572464,0.5192307692307693,0.5060589429054257,0.7209683060646057,0.5279373251382632
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||||
B5_mofe_mlp,42,text_20,0.2,learned_router,728,0.5065384615384615,0.6304945054945055,0.5904030390809835,0.6350097060203552,0.5945970800346047
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||||
B5_mofe_mlp,42,text_20,0.2,T,728,0.4137362837791443,0.6277472527472527,0.5834715774578197,0.6387249231338501,0.5959559379397134
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||||
B5_mofe_mlp,42,text_20,0.2,A,728,0.47049450874328613,0.47115384615384615,0.2975569493673755,0.7751386761665344,0.17787621670831064
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||||
B5_mofe_mlp,42,text_20,0.2,V,728,0.44483518600463867,0.49313186813186816,0.3957467065496128,0.7714186310768127,0.22587166430826042
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||||
B5_mofe_mlp,42,text_20,0.2,TA,728,0.377692312002182,0.6043956043956044,0.5611937927949194,0.6714186668395996,0.5678669128762814
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||||
B5_mofe_mlp,42,text_20,0.2,TV,728,0.35653847455978394,0.5686813186813187,0.5239313100098085,0.681026816368103,0.526936547599484
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||||
B5_mofe_mlp,42,text_20,0.2,AV,728,0.44483518600463867,0.39972527472527475,0.31990146004230513,0.8130425810813904,0.2707806717799165
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||||
B5_mofe_mlp,42,text_20,0.2,TAV,728,0.35653847455978394,0.5192307692307693,0.49528792280719197,0.7405415773391724,0.5088571560275247
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||||
B5_mofe_mlp,42,audio_20,0.2,learned_router,728,0.5117582417582418,0.6483516483516484,0.6152893789223305,0.6198974251747131,0.6158397838233138
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||||
B5_mofe_mlp,42,audio_20,0.2,T,728,0.5117582678794861,0.6277472527472527,0.5934285449238298,0.6425583362579346,0.6129603628587058
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||||
B5_mofe_mlp,42,audio_20,0.2,A,728,0.37777474522590637,0.5370879120879121,0.4088556651206101,0.721038818359375,0.408803633397513
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||||
B5_mofe_mlp,42,audio_20,0.2,V,728,0.44483518600463867,0.5027472527472527,0.4043940692076286,0.7664347290992737,0.24638264842704208
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||||
B5_mofe_mlp,42,audio_20,0.2,TA,728,0.37777474522590637,0.6291208791208791,0.5983548479511946,0.6565340757369995,0.6034848427820116
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||||
B5_mofe_mlp,42,audio_20,0.2,TV,728,0.44483518600463867,0.5618131868131868,0.5278821116181079,0.6707059144973755,0.5439704521908111
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||||
B5_mofe_mlp,42,audio_20,0.2,AV,728,0.35697802901268005,0.49175824175824173,0.4044220197597692,0.7304497957229614,0.46939738334691383
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||||
B5_mofe_mlp,42,audio_20,0.2,TAV,728,0.35697802901268005,0.554945054945055,0.5389342277853322,0.683380126953125,0.5631088893669088
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||||
B5_mofe_mlp,42,vision_20,0.2,learned_router,728,0.5117582417582418,0.6497252747252747,0.6161050291578356,0.6227805614471436,0.6170723967407132
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||||
B5_mofe_mlp,42,vision_20,0.2,T,728,0.5117582678794861,0.6304945054945055,0.595665938533476,0.6456263065338135,0.612921271986715
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||||
B5_mofe_mlp,42,vision_20,0.2,A,728,0.47049450874328613,0.4739010989010989,0.294076640863259,0.772672712802887,0.19172033154149434
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||||
B5_mofe_mlp,42,vision_20,0.2,V,728,0.3548901081085205,0.5494505494505495,0.4673960507937731,0.7191774845123291,0.4004459126810772
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||||
B5_mofe_mlp,42,vision_20,0.2,TA,728,0.47049450874328613,0.6071428571428571,0.5708690749466393,0.6775083541870117,0.5974902100142974
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||||
B5_mofe_mlp,42,vision_20,0.2,TV,728,0.3548901081085205,0.6016483516483516,0.5649164229707409,0.647191047668457,0.5713132865281553
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||||
B5_mofe_mlp,42,vision_20,0.2,AV,728,0.3548901081085205,0.5137362637362637,0.43167042702402014,0.7291663289070129,0.416186430649655
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||||
B5_mofe_mlp,42,vision_20,0.2,TAV,728,0.3548901081085205,0.5741758241758241,0.5579426783722908,0.6710066795349121,0.5582887705143701
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,learned_router,728,0.5117582417582418,0.6456043956043956,0.6124517381483326,0.6248074173927307,0.6073068166652785
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,T,728,0.5117582678794861,0.6291208791208791,0.5952612725131757,0.6444122791290283,0.6129037391710341
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,A,728,0.3742307722568512,0.5288461538461539,0.393885105990035,0.7293428778648376,0.3882759877201428
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,V,728,0.3539285659790039,0.5494505494505495,0.4675111779446084,0.7149078249931335,0.41871289651004223
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,TA,728,0.3742307722568512,0.6195054945054945,0.5844559446078783,0.669805645942688,0.600856133553038
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,TV,728,0.3539285659790039,0.5892857142857143,0.5537996616712025,0.6531057357788086,0.5563709753247387
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,AV,728,0.3539285659790039,0.4945054945054945,0.4048075528799828,0.7323312163352966,0.42436332986946057
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||||
B5_mofe_mlp,42,audio_vision_20,0.2,TAV,728,0.3539285659790039,0.5535714285714286,0.5374035508293326,0.6750969290733337,0.5556165001105868
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,learned_router,728,0.41145604395604396,0.6401098901098901,0.6082957983542778,0.6285881400108337,0.6113174288636467
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,T,728,0.41145604848861694,0.6112637362637363,0.5753999256800798,0.6470811367034912,0.6110403575185562
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,A,728,0.37502747774124146,0.48214285714285715,0.30971805746653613,0.7708896994590759,0.19843845587271233
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,V,728,0.3545604348182678,0.5,0.40444384179778897,0.768601655960083,0.2478532037462523
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,TA,728,0.37502747774124146,0.6126373626373627,0.581822149187397,0.6791433691978455,0.5855705717441732
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,TV,728,0.3545604348182678,0.5714285714285714,0.5350638931866368,0.6752635836601257,0.5391820306204274
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,AV,728,0.3545604348182678,0.4065934065934066,0.33361946481005195,0.7985524535179138,0.28911163355771957
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||||
B5_mofe_mlp,42,all_modalities_20,0.2,TAV,728,0.3545604348182678,0.5137362637362637,0.5016717439879469,0.7235588431358337,0.5228808277462639
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||||
B5_mofe_mlp,42,text_30,0.3,learned_router,728,0.5034615384615385,0.614010989010989,0.5665382052109811,0.6587778925895691,0.5712246625860047
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B5_mofe_mlp,42,text_30,0.3,T,728,0.36975276470184326,0.6002747252747253,0.5489214966247952,0.6610612273216248,0.5660733797289579
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||||
B5_mofe_mlp,42,text_30,0.3,A,728,0.47049450874328613,0.4739010989010989,0.29743008078567407,0.776188850402832,0.16784848141204534
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B5_mofe_mlp,42,text_30,0.3,V,728,0.44483518600463867,0.489010989010989,0.3906705384925391,0.7730352282524109,0.21533838045151854
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B5_mofe_mlp,42,text_30,0.3,TA,728,0.3367857336997986,0.5769230769230769,0.5309590282919976,0.6845227479934692,0.5380879936631464
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B5_mofe_mlp,42,text_30,0.3,TV,728,0.3170604407787323,0.5563186813186813,0.5074245114833101,0.6991907358169556,0.5079542890645365
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B5_mofe_mlp,42,text_30,0.3,AV,728,0.44483518600463867,0.38873626373626374,0.3106438181055198,0.8153451681137085,0.2564790729278157
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B5_mofe_mlp,42,text_30,0.3,TAV,728,0.3170604407787323,0.510989010989011,0.48202998092174165,0.7513630390167236,0.48075890078323275
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||||
B5_mofe_mlp,42,audio_30,0.3,learned_router,728,0.5117582417582418,0.6414835164835165,0.6099992622632019,0.6212661862373352,0.6127160322638576
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||||
B5_mofe_mlp,42,audio_30,0.3,T,728,0.5117582678794861,0.6304945054945055,0.5962642544403453,0.6413890719413757,0.6140594602256363
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B5_mofe_mlp,42,audio_30,0.3,A,728,0.32620880007743835,0.5480769230769231,0.4494048835498772,0.7181518077850342,0.4130353082081023
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B5_mofe_mlp,42,audio_30,0.3,V,728,0.44483518600463867,0.5027472527472527,0.40552179812400446,0.7659018635749817,0.24744836243929447
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B5_mofe_mlp,42,audio_30,0.3,TA,728,0.32620880007743835,0.6291208791208791,0.5964728532922603,0.6501738429069519,0.6030688423259514
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B5_mofe_mlp,42,audio_30,0.3,TV,728,0.44483518600463867,0.5618131868131868,0.5278372031251927,0.6705804467201233,0.5438638236128189
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B5_mofe_mlp,42,audio_30,0.3,AV,728,0.3069230914115906,0.49862637362637363,0.42544608223551644,0.7236812710762024,0.4526082943905184
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B5_mofe_mlp,42,audio_30,0.3,TAV,728,0.3069230914115906,0.5673076923076923,0.5511576680296482,0.6794568300247192,0.5516785851487167
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B5_mofe_mlp,42,vision_30,0.3,learned_router,728,0.5117582417582418,0.6442307692307693,0.6100360167586674,0.6305182576179504,0.6127016976409972
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B5_mofe_mlp,42,vision_30,0.3,T,728,0.5117582678794861,0.6263736263736264,0.59178963181016,0.6464172005653381,0.6124406407087638
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B5_mofe_mlp,42,vision_30,0.3,A,728,0.47049450874328613,0.47527472527472525,0.29307320983548674,0.7725724577903748,0.18981337716798075
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B5_mofe_mlp,42,vision_30,0.3,V,728,0.31381869316101074,0.5480769230769231,0.46141777713440435,0.7053895592689514,0.4504351953464994
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B5_mofe_mlp,42,vision_30,0.3,TA,728,0.47049450874328613,0.6112637362637363,0.5755727285311548,0.6785207986831665,0.5965958774703438
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B5_mofe_mlp,42,vision_30,0.3,TV,728,0.31381869316101074,0.5947802197802198,0.5518425273811883,0.6574218273162842,0.5668784897408216
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B5_mofe_mlp,42,vision_30,0.3,AV,728,0.31381869316101074,0.5027472527472527,0.413102983693412,0.7221376299858093,0.44235786176147723
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B5_mofe_mlp,42,vision_30,0.3,TAV,728,0.31381869316101074,0.5810439560439561,0.5627987997604266,0.6714197397232056,0.5504938666999736
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,learned_router,728,0.5117582417582418,0.6538461538461539,0.6220936984876739,0.6240691542625427,0.6123047776384958
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,T,728,0.5117582678794861,0.6291208791208791,0.5956657591699687,0.6447410583496094,0.6124816718027329
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,A,728,0.3259340822696686,0.5412087912087912,0.4293427018964002,0.7119898796081543,0.46116924292994144
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,V,728,0.30848902463912964,0.5741758241758241,0.5081685315054737,0.7036085724830627,0.46865253704666515
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,TA,728,0.3259340822696686,0.6167582417582418,0.5796313859552673,0.6652615070343018,0.6066108168106552
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,TV,728,0.30848902463912964,0.6085164835164835,0.5747678972005031,0.6532444953918457,0.5685189504949397
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,AV,728,0.30848902463912964,0.5178571428571429,0.4479560935960237,0.704010009765625,0.4737609457990894
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||||
B5_mofe_mlp,42,audio_vision_30,0.3,TAV,728,0.30848902463912964,0.5769230769230769,0.5590219753958139,0.6671831011772156,0.5613400203043469
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,learned_router,728,0.3595054945054945,0.6442307692307693,0.6106062664769548,0.6119968891143799,0.6240023475516322
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,T,728,0.3595055043697357,0.6332417582417582,0.5994013685816965,0.6420187950134277,0.6142476274070523
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,A,728,0.326043963432312,0.4876373626373626,0.32114976052878363,0.7629672288894653,0.24577611782666536
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,V,728,0.3076648414134979,0.5137362637362637,0.41564992061683226,0.7619249224662781,0.26280751782695616
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,TA,728,0.326043963432312,0.6277472527472527,0.5901208902602798,0.6717715263366699,0.6055637792894115
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,TV,728,0.3076648414134979,0.5851648351648352,0.550384612243989,0.6579670906066895,0.5550817131264711
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,AV,728,0.3076648414134979,0.43131868131868134,0.3524060719327709,0.7886312007904053,0.2950171316134991
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||||
B5_mofe_mlp,42,all_modalities_30,0.3,TAV,728,0.3076648414134979,0.5206043956043956,0.5084554432330729,0.7108278274536133,0.5347220240307088
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||||
B5_mofe_mlp,3407,clean,0.0,learned_router,728,0.5117582417582418,0.635989010989011,0.604973907499834,0.6324349045753479,0.6151046626873287
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||||
B5_mofe_mlp,3407,clean,0.0,T,728,0.5117582678794861,0.6002747252747253,0.589715106019248,0.6271728873252869,0.6222406477372165
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||||
B5_mofe_mlp,3407,clean,0.0,A,728,0.47049450874328613,0.46703296703296704,0.25617731189594245,0.8055213093757629,0.08527234954826798
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||||
B5_mofe_mlp,3407,clean,0.0,V,728,0.44483518600463867,0.45879120879120877,0.3911083700819353,0.7868513464927673,0.2733494259442715
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||||
B5_mofe_mlp,3407,clean,0.0,TA,728,0.47049450874328613,0.5796703296703297,0.5637105051146315,0.6420981884002686,0.5835249000576797
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||||
B5_mofe_mlp,3407,clean,0.0,TV,728,0.44483518600463867,0.6153846153846154,0.5641846149831432,0.6430084109306335,0.5929149001529713
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||||
B5_mofe_mlp,3407,clean,0.0,AV,728,0.44483518600463867,0.3791208791208791,0.31403029968176926,0.8854933381080627,0.27891622253907705
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||||
B5_mofe_mlp,3407,clean,0.0,TAV,728,0.44483518600463867,0.5879120879120879,0.5681219195313041,0.6709685921669006,0.5645502331565663
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||||
B5_mofe_mlp,3407,text_10,0.1,learned_router,728,0.509010989010989,0.6318681318681318,0.5933228635123383,0.633339524269104,0.6112815975781888
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||||
B5_mofe_mlp,3407,text_10,0.1,T,728,0.46123626828193665,0.614010989010989,0.5962559055831377,0.6278678774833679,0.6178578184774396
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||||
B5_mofe_mlp,3407,text_10,0.1,A,728,0.47049450874328613,0.4642857142857143,0.24969978803929094,0.8068049550056458,0.080513190196943
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||||
B5_mofe_mlp,3407,text_10,0.1,V,728,0.44483518600463867,0.4574175824175824,0.3878406396990897,0.7909943461418152,0.2623676162284545
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||||
B5_mofe_mlp,3407,text_10,0.1,TA,728,0.4227197766304016,0.5879120879120879,0.5646643159293967,0.6490334868431091,0.5744750721425774
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||||
B5_mofe_mlp,3407,text_10,0.1,TV,728,0.39942309260368347,0.6085164835164835,0.5474885374714241,0.6448301672935486,0.5895230801704665
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||||
B5_mofe_mlp,3407,text_10,0.1,AV,728,0.44483518600463867,0.37774725274725274,0.3110187465790914,0.8889135718345642,0.2696459458776994
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||||
B5_mofe_mlp,3407,text_10,0.1,TAV,728,0.39942309260368347,0.5934065934065934,0.563693177045021,0.6679768562316895,0.5622421569025232
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||||
B5_mofe_mlp,3407,audio_10,0.1,learned_router,728,0.5117582417582418,0.635989010989011,0.6042690508274062,0.6318331956863403,0.6144226173077325
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||||
B5_mofe_mlp,3407,audio_10,0.1,T,728,0.5117582678794861,0.5989010989010989,0.5878169018954168,0.6271204948425293,0.622383546006487
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||||
B5_mofe_mlp,3407,audio_10,0.1,A,728,0.422802209854126,0.5027472527472527,0.332656408166132,0.7686276435852051,0.25398532291213505
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||||
B5_mofe_mlp,3407,audio_10,0.1,V,728,0.44483518600463867,0.45604395604395603,0.38920601362461826,0.7875474095344543,0.2726621335461414
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||||
B5_mofe_mlp,3407,audio_10,0.1,TA,728,0.422802209854126,0.5947802197802198,0.5806242036699651,0.6359114050865173,0.5923569117539921
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||||
B5_mofe_mlp,3407,audio_10,0.1,TV,728,0.44483518600463867,0.6167582417582418,0.5663217661957952,0.6429393291473389,0.5927652831204141
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||||
B5_mofe_mlp,3407,audio_10,0.1,AV,728,0.3992857336997986,0.44505494505494503,0.40079404466501245,0.8398518562316895,0.37350789652686583
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||||
B5_mofe_mlp,3407,audio_10,0.1,TAV,728,0.3992857336997986,0.5879120879120879,0.5677938460265421,0.6635177135467529,0.5747748964548253
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||||
B5_mofe_mlp,3407,vision_10,0.1,learned_router,728,0.5117582417582418,0.6387362637362637,0.6078729015399154,0.6297808885574341,0.6157341493803992
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||||
B5_mofe_mlp,3407,vision_10,0.1,T,728,0.5117582678794861,0.5989010989010989,0.5881686695855791,0.6271765232086182,0.6224112929540812
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||||
B5_mofe_mlp,3407,vision_10,0.1,A,728,0.47049450874328613,0.4697802197802198,0.2617495652772756,0.8053902387619019,0.08562704392462114
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||||
B5_mofe_mlp,3407,vision_10,0.1,V,728,0.39975276589393616,0.5164835164835165,0.4530382033974704,0.7460650205612183,0.37016954440873484
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||||
B5_mofe_mlp,3407,vision_10,0.1,TA,728,0.47049450874328613,0.5810439560439561,0.5652874494272252,0.6420679092407227,0.5835241242239276
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||||
B5_mofe_mlp,3407,vision_10,0.1,TV,728,0.39975276589393616,0.6208791208791209,0.5716893090185614,0.636868417263031,0.5996523024591878
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||||
B5_mofe_mlp,3407,vision_10,0.1,AV,728,0.39975276589393616,0.4340659340659341,0.3798771393241414,0.8302300572395325,0.3660266205867799
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||||
B5_mofe_mlp,3407,vision_10,0.1,TAV,728,0.39975276589393616,0.5975274725274725,0.5773266951804078,0.6591137051582336,0.5739229519759457
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,learned_router,728,0.5117582417582418,0.625,0.5961079542334627,0.630139172077179,0.614822589976647
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,T,728,0.5117582678794861,0.6002747252747253,0.5895426241854899,0.6275323629379272,0.6220930103186073
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,A,728,0.42197802662849426,0.4793956043956044,0.2964038513186514,0.7789897918701172,0.23988959094939177
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,V,728,0.39879122376441956,0.4945054945054945,0.44061682531723784,0.7518568634986877,0.3852922869623105
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,TA,728,0.42197802662849426,0.5906593406593407,0.5759372217914477,0.6386086344718933,0.5889149366423129
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,TV,728,0.39879122376441956,0.6195054945054945,0.5730831708901883,0.6402206420898438,0.5971609331392899
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,AV,728,0.39879122376441956,0.4409340659340659,0.39365944462354036,0.8360045552253723,0.3745781671523048
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||||
B5_mofe_mlp,3407,audio_vision_10,0.1,TAV,728,0.39879122376441956,0.5879120879120879,0.5702051410805352,0.6638662219047546,0.5713070522068541
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,learned_router,728,0.4610164835164835,0.6195054945054945,0.5890880499595165,0.6359822750091553,0.6113081341411937
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,T,728,0.4610165059566498,0.5934065934065934,0.5840003133946626,0.63011234998703,0.6190677754940976
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,A,728,0.4225274920463562,0.47115384615384615,0.2646409174971828,0.8042469024658203,0.08459586170402346
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,V,728,0.399478018283844,0.46016483516483514,0.39465376804402846,0.7862517237663269,0.2773311673393334
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,TA,728,0.4225274920463562,0.5824175824175825,0.5671818574180514,0.6445117592811584,0.5822325728126405
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,TV,728,0.399478018283844,0.6043956043956044,0.5508070001152509,0.6478139162063599,0.5896831592571647
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,AV,728,0.399478018283844,0.3873626373626374,0.32667745632365675,0.8781699538230896,0.28384176543794837
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||||
B5_mofe_mlp,3407,all_modalities_10,0.1,TAV,728,0.399478018283844,0.5796703296703297,0.5603794485883429,0.6692947745323181,0.5686062320667473
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||||
B5_mofe_mlp,3407,text_20,0.2,learned_router,728,0.5066758241758241,0.6195054945054945,0.5755820027236789,0.6454524993896484,0.593560555068977
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||||
B5_mofe_mlp,3407,text_20,0.2,T,728,0.4073077142238617,0.6016483516483516,0.5744089403315806,0.6390801072120667,0.6021358689203483
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||||
B5_mofe_mlp,3407,text_20,0.2,A,728,0.47049450874328613,0.4642857142857143,0.2494552539431357,0.8059768080711365,0.07746170464833917
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||||
B5_mofe_mlp,3407,text_20,0.2,V,728,0.44483518600463867,0.45467032967032966,0.38380648966660313,0.793641984462738,0.24830679616913864
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||||
B5_mofe_mlp,3407,text_20,0.2,TA,728,0.3711263835430145,0.5741758241758241,0.5418661031211773,0.6627365946769714,0.560477116430549
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||||
B5_mofe_mlp,3407,text_20,0.2,TV,728,0.3507142961025238,0.603021978021978,0.5357923985725986,0.6560191512107849,0.57324278460567
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||||
B5_mofe_mlp,3407,text_20,0.2,AV,728,0.44483518600463867,0.3791208791208791,0.3126586105031628,0.8910257816314697,0.2565337001789869
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||||
B5_mofe_mlp,3407,text_20,0.2,TAV,728,0.3507142961025238,0.5934065934065934,0.5604543054498898,0.6754387021064758,0.5450045495235731
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||||
B5_mofe_mlp,3407,audio_20,0.2,learned_router,728,0.5117582417582418,0.6332417582417582,0.6046231856798019,0.6310903429985046,0.6172434069189507
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||||
B5_mofe_mlp,3407,audio_20,0.2,T,728,0.5117582678794861,0.6002747252747253,0.5893745342941709,0.6272591948509216,0.6221016536867588
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||||
B5_mofe_mlp,3407,audio_20,0.2,A,728,0.3748626410961151,0.4945054945054945,0.3373484461000103,0.7447602152824402,0.3567551983127843
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||||
B5_mofe_mlp,3407,audio_20,0.2,V,728,0.44483518600463867,0.46016483516483514,0.3944283930013793,0.788540244102478,0.2723841073830063
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||||
B5_mofe_mlp,3407,audio_20,0.2,TA,728,0.3748626410961151,0.5975274725274725,0.5831680958487365,0.6350200176239014,0.5940989862125469
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||||
B5_mofe_mlp,3407,audio_20,0.2,TV,728,0.44483518600463867,0.6167582417582418,0.5667282248122798,0.6437039375305176,0.5927169318926079
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||||
B5_mofe_mlp,3407,audio_20,0.2,AV,728,0.35401099920272827,0.4697802197802198,0.42693867646678624,0.8040833473205566,0.41986353119227654
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||||
B5_mofe_mlp,3407,audio_20,0.2,TAV,728,0.35401099920272827,0.6002747252747253,0.5813735202449936,0.6587744355201721,0.5783157554155207
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||||
B5_mofe_mlp,3407,vision_20,0.2,learned_router,728,0.5117582417582418,0.635989010989011,0.6063745521197687,0.6304876804351807,0.6140966219851783
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||||
B5_mofe_mlp,3407,vision_20,0.2,T,728,0.5117582678794861,0.6002747252747253,0.5892252758196194,0.6273123025894165,0.6225083846238101
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||||
B5_mofe_mlp,3407,vision_20,0.2,A,728,0.47049450874328613,0.4684065934065934,0.25920850508591314,0.8053038716316223,0.085792392341107
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||||
B5_mofe_mlp,3407,vision_20,0.2,V,728,0.3525000214576721,0.5288461538461539,0.4720058888479941,0.7252842783927917,0.41317305592752934
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||||
B5_mofe_mlp,3407,vision_20,0.2,TA,728,0.47049450874328613,0.5824175824175825,0.5670673740607254,0.6420120000839233,0.584068084198822
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||||
B5_mofe_mlp,3407,vision_20,0.2,TV,728,0.3525000214576721,0.625,0.5781351467902999,0.6339038610458374,0.5999732210847242
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||||
B5_mofe_mlp,3407,vision_20,0.2,AV,728,0.3525000214576721,0.47802197802197804,0.4364142415752362,0.7915685176849365,0.4020386709009841
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||||
B5_mofe_mlp,3407,vision_20,0.2,TAV,728,0.3525000214576721,0.6181318681318682,0.5982469512967439,0.656253457069397,0.5726154586560915
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,learned_router,728,0.5117582417582418,0.635989010989011,0.609224910808655,0.6240155696868896,0.6185045310430713
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,T,728,0.5117582678794861,0.5989010989010989,0.5883115478052187,0.6270718574523926,0.6227611193021018
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,A,728,0.36782968044281006,0.5123626373626373,0.3814657210401891,0.7518494725227356,0.33531566843891375
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,V,728,0.34728023409843445,0.5247252747252747,0.4843248302906597,0.7358435392379761,0.4214118417347598
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,TA,728,0.36782968044281006,0.6002747252747253,0.5892792851694453,0.6287823915481567,0.6006773690433412
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,TV,728,0.34728023409843445,0.6332417582417582,0.5964419732456347,0.6303028464317322,0.6076400918884116
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,AV,728,0.34728023409843445,0.46565934065934067,0.4355944055944056,0.802980363368988,0.416563986982085
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||||
B5_mofe_mlp,3407,audio_vision_20,0.2,TAV,728,0.34728023409843445,0.6002747252747253,0.5862363095320736,0.6544463038444519,0.585378576750997
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,learned_router,728,0.40958791208791206,0.6332417582417582,0.6079307048305954,0.634419858455658,0.6044717331613441
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,T,728,0.40958791971206665,0.6002747252747253,0.5899048320687862,0.6346542835235596,0.6100138467500781
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,A,728,0.3732692301273346,0.4739010989010989,0.27165625210557365,0.8040054440498352,0.10424704916947851
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,V,728,0.3524450659751892,0.4642857142857143,0.40252151018656984,0.7802431583404541,0.29135073297647346
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,TA,728,0.3732692301273346,0.5686813186813187,0.5572575422788313,0.6487622261047363,0.572519010283675
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,TV,728,0.3524450659751892,0.6126373626373627,0.5629491230638092,0.6498149037361145,0.5810132494000526
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,AV,728,0.3524450659751892,0.3956043956043956,0.3405710346065853,0.8701844215393066,0.3057071236393479
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||||
B5_mofe_mlp,3407,all_modalities_20,0.2,TAV,728,0.3524450659751892,0.5837912087912088,0.5631923344724951,0.6739726066589355,0.559728632496238
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||||
B5_mofe_mlp,3407,text_30,0.3,learned_router,728,0.5033791208791208,0.6181318681318682,0.5733540937906745,0.6566742658615112,0.566892564181419
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||||
B5_mofe_mlp,3407,text_30,0.3,T,728,0.36063188314437866,0.6112637362637363,0.5806932321558671,0.6485380530357361,0.579561962998976
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||||
B5_mofe_mlp,3407,text_30,0.3,A,728,0.47049450874328613,0.46703296703296704,0.2536900771342752,0.8093824982643127,0.062449242058257734
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||||
B5_mofe_mlp,3407,text_30,0.3,V,728,0.44483518600463867,0.4409340659340659,0.3710188660549014,0.7965743541717529,0.2468807094370837
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||||
B5_mofe_mlp,3407,text_30,0.3,TA,728,0.32774725556373596,0.592032967032967,0.5537539943729123,0.6646007299423218,0.5395408779465738
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||||
B5_mofe_mlp,3407,text_30,0.3,TV,728,0.30873626470565796,0.6016483516483516,0.5385391277047284,0.6617969870567322,0.5533827408893808
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||||
B5_mofe_mlp,3407,text_30,0.3,AV,728,0.44483518600463867,0.37225274725274726,0.3029182824443429,0.8928882479667664,0.25637364632868326
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||||
B5_mofe_mlp,3407,text_30,0.3,TAV,728,0.30873626470565796,0.5865384615384616,0.5490273643806375,0.6738438010215759,0.5345429351694087
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||||
B5_mofe_mlp,3407,audio_30,0.3,learned_router,728,0.5117582417582418,0.6332417582417582,0.604260667390971,0.6289573907852173,0.6173815327526297
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||||
B5_mofe_mlp,3407,audio_30,0.3,T,728,0.5117582678794861,0.6002747252747253,0.5893745342941709,0.6269524693489075,0.6225360827025238
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||||
B5_mofe_mlp,3407,audio_30,0.3,A,728,0.3245879113674164,0.532967032967033,0.41756519321424274,0.7341850399971008,0.41121987797045906
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||||
B5_mofe_mlp,3407,audio_30,0.3,V,728,0.44483518600463867,0.45054945054945056,0.3832106337593439,0.788564920425415,0.27355794624988927
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||||
B5_mofe_mlp,3407,audio_30,0.3,TA,728,0.3245879113674164,0.6085164835164835,0.5930238521146932,0.6325163841247559,0.5979866380346056
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||||
B5_mofe_mlp,3407,audio_30,0.3,TV,728,0.44483518600463867,0.6112637362637363,0.5583419641348294,0.6421341300010681,0.5937514966892242
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||||
B5_mofe_mlp,3407,audio_30,0.3,AV,728,0.30483517050743103,0.5,0.4623444097193838,0.7733940482139587,0.4553589450889685
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||||
B5_mofe_mlp,3407,audio_30,0.3,TAV,728,0.30483517050743103,0.614010989010989,0.5938581135634877,0.6490943431854248,0.594392630535773
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||||
B5_mofe_mlp,3407,vision_30,0.3,learned_router,728,0.5117582417582418,0.6332417582417582,0.6016029959347541,0.6318032145500183,0.6125144009888801
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||||
B5_mofe_mlp,3407,vision_30,0.3,T,728,0.5117582678794861,0.5989010989010989,0.5879942456720697,0.627319872379303,0.622716023566736
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||||
B5_mofe_mlp,3407,vision_30,0.3,A,728,0.47049450874328613,0.4697802197802198,0.26181694968773733,0.8051190972328186,0.08667342142486818
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||||
B5_mofe_mlp,3407,vision_30,0.3,V,728,0.3087087869644165,0.5233516483516484,0.461764143838227,0.7223021984100342,0.4261833345686536
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||||
B5_mofe_mlp,3407,vision_30,0.3,TA,728,0.47049450874328613,0.5824175824175825,0.5672280279314932,0.6419576406478882,0.5838877593870844
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||||
B5_mofe_mlp,3407,vision_30,0.3,TV,728,0.3087087869644165,0.6112637362637363,0.5662069378393744,0.641978919506073,0.5924386504061155
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||||
B5_mofe_mlp,3407,vision_30,0.3,AV,728,0.3087087869644165,0.49862637362637363,0.445456810889948,0.7776786088943481,0.42160082881328553
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||||
B5_mofe_mlp,3407,vision_30,0.3,TAV,728,0.3087087869644165,0.6071428571428571,0.5854633810737848,0.6539671421051025,0.5750920229415292
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,learned_router,728,0.5117582417582418,0.6318681318681318,0.6067614810631058,0.6228161454200745,0.6214083492458665
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,T,728,0.5117582678794861,0.6002747252747253,0.5893745342941709,0.627665102481842,0.6221383829594522
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,A,728,0.324972540140152,0.5425824175824175,0.43415828421831115,0.7195268273353577,0.4252793587336247
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,V,728,0.30618131160736084,0.5521978021978022,0.5104487621775328,0.7024396657943726,0.48245166107283655
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,TA,728,0.324972540140152,0.6085164835164835,0.5960454962258536,0.627300500869751,0.605465763886298
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,TV,728,0.30618131160736084,0.6195054945054945,0.5821910607231708,0.6338788270950317,0.6053651346534237
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,AV,728,0.30618131160736084,0.510989010989011,0.4810449552418117,0.7675954699516296,0.46180909475521414
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||||
B5_mofe_mlp,3407,audio_vision_30,0.3,TAV,728,0.30618131160736084,0.6085164835164835,0.5928020993486814,0.6524761319160461,0.5899472144346922
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,learned_router,728,0.3557967032967033,0.6222527472527473,0.5949881199577279,0.6458109617233276,0.5977780881361412
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,T,728,0.3557967245578766,0.6057692307692307,0.5973699542180001,0.636671781539917,0.6031830619040961
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,A,728,0.32255494594573975,0.47802197802197804,0.2858992684718562,0.7997276186943054,0.12003216546779098
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,V,728,0.3045879304409027,0.49175824175824173,0.4332501168084348,0.778567910194397,0.28114115860320466
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,TA,728,0.32255494594573975,0.5755494505494505,0.5618376925923627,0.6488231420516968,0.5646885904319525
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,TV,728,0.3045879304409027,0.6153846153846154,0.569951909037207,0.6524090766906738,0.5765150164354017
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,AV,728,0.3045879304409027,0.41208791208791207,0.3552498095654271,0.8604830503463745,0.28184821072646954
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||||
B5_mofe_mlp,3407,all_modalities_30,0.3,TAV,728,0.3045879304409027,0.5741758241758241,0.5572916475321001,0.676213800907135,0.54624389958209
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||||
B5_mofe_mlp,2026,clean,0.0,learned_router,728,0.5117582417582418,0.6318681318681318,0.596526187825028,0.6597291827201843,0.603269634378733
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||||
B5_mofe_mlp,2026,clean,0.0,T,728,0.5117582678794861,0.6126373626373627,0.596773495897157,0.6489740014076233,0.601146379126596
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||||
B5_mofe_mlp,2026,clean,0.0,A,728,0.47049450874328613,0.4725274725274725,0.2753954425047768,0.8250412344932556,0.2298903631499931
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||||
B5_mofe_mlp,2026,clean,0.0,V,728,0.44483518600463867,0.5151098901098901,0.41609693688045696,0.7419555187225342,0.33524138002400866
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||||
B5_mofe_mlp,2026,clean,0.0,TA,728,0.47049450874328613,0.592032967032967,0.5532162058371736,0.6664567589759827,0.5597609050774838
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||||
B5_mofe_mlp,2026,clean,0.0,TV,728,0.44483518600463867,0.592032967032967,0.5774206516713903,0.7040247917175293,0.5664710859024277
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||||
B5_mofe_mlp,2026,clean,0.0,AV,728,0.44483518600463867,0.3626373626373626,0.34907979624206836,0.8443424105644226,0.23675834043024976
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||||
B5_mofe_mlp,2026,clean,0.0,TAV,728,0.44483518600463867,0.5370879120879121,0.4651554172647243,0.800514817237854,0.5127572796173613
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||||
B5_mofe_mlp,2026,text_10,0.1,learned_router,728,0.5091208791208791,0.6332417582417582,0.5928689292978023,0.6584991812705994,0.596161006853697
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||||
B5_mofe_mlp,2026,text_10,0.1,T,728,0.46167582273483276,0.6126373626373627,0.5930164703753459,0.6494342088699341,0.5946751987953215
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||||
B5_mofe_mlp,2026,text_10,0.1,A,728,0.47049450874328613,0.4725274725274725,0.27541290783115796,0.8262399435043335,0.22445379743900615
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||||
B5_mofe_mlp,2026,text_10,0.1,V,728,0.44483518600463867,0.5123626373626373,0.41266149205541813,0.7444264888763428,0.3297960384984079
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||||
B5_mofe_mlp,2026,text_10,0.1,TA,728,0.4230494499206543,0.5837912087912088,0.5397729831672579,0.6658428907394409,0.5527226923735943
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||||
B5_mofe_mlp,2026,text_10,0.1,TV,728,0.4000000059604645,0.592032967032967,0.571111408272237,0.6985095739364624,0.5560292387489061
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||||
B5_mofe_mlp,2026,text_10,0.1,AV,728,0.44483518600463867,0.3585164835164835,0.34496753089852183,0.8458796739578247,0.23343561887490413
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||||
B5_mofe_mlp,2026,text_10,0.1,TAV,728,0.4000000059604645,0.5384615384615384,0.4615912536399786,0.7843563556671143,0.4964630609894201
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||||
B5_mofe_mlp,2026,audio_10,0.1,learned_router,728,0.5117582417582418,0.6332417582417582,0.5971419540706502,0.658007025718689,0.6047899431200526
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||||
B5_mofe_mlp,2026,audio_10,0.1,T,728,0.5117582678794861,0.6112637362637363,0.594775223911222,0.6496217846870422,0.601103231343751
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||||
B5_mofe_mlp,2026,audio_10,0.1,A,728,0.42263737320899963,0.489010989010989,0.30986648206415496,0.795183539390564,0.32899912608575077
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||||
B5_mofe_mlp,2026,audio_10,0.1,V,728,0.44483518600463867,0.5164835164835165,0.41734454924869885,0.7415561079978943,0.3356207820136009
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||||
B5_mofe_mlp,2026,audio_10,0.1,TA,728,0.42263737320899963,0.5906593406593407,0.5523948427986319,0.6616610288619995,0.5656969509728144
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||||
B5_mofe_mlp,2026,audio_10,0.1,TV,728,0.44483518600463867,0.5906593406593407,0.5756793112725316,0.7050058841705322,0.567017826103781
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||||
B5_mofe_mlp,2026,audio_10,0.1,AV,728,0.3998076915740967,0.40796703296703296,0.4021505731323723,0.8058489561080933,0.33914515576905724
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||||
B5_mofe_mlp,2026,audio_10,0.1,TAV,728,0.3998076915740967,0.5604395604395604,0.5020907193394417,0.7697135210037231,0.5332348404594554
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||||
B5_mofe_mlp,2026,vision_10,0.1,learned_router,728,0.5117582417582418,0.6277472527472527,0.5919759280299669,0.6596941947937012,0.6023122800724011
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||||
B5_mofe_mlp,2026,vision_10,0.1,T,728,0.5117582678794861,0.6112637362637363,0.5949280494683542,0.648731529712677,0.6010584699954675
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||||
B5_mofe_mlp,2026,vision_10,0.1,A,728,0.47049450874328613,0.4725274725274725,0.2753954425047768,0.8233988285064697,0.2309789025689641
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||||
B5_mofe_mlp,2026,vision_10,0.1,V,728,0.3984340727329254,0.5398351648351648,0.43853463696042566,0.7145515084266663,0.4295200877890959
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||||
B5_mofe_mlp,2026,vision_10,0.1,TA,728,0.47049450874328613,0.592032967032967,0.5532162058371736,0.6668615937232971,0.5594488575507512
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||||
B5_mofe_mlp,2026,vision_10,0.1,TV,728,0.3984340727329254,0.6016483516483516,0.5819547002883038,0.6787747144699097,0.5779704289995252
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||||
B5_mofe_mlp,2026,vision_10,0.1,AV,728,0.3984340727329254,0.4258241758241758,0.42253912572720753,0.7936479449272156,0.3612784148549423
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||||
B5_mofe_mlp,2026,vision_10,0.1,TAV,728,0.3984340727329254,0.5714285714285714,0.5087225335512859,0.760180652141571,0.5350946399361437
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,learned_router,728,0.5117582417582418,0.6291208791208791,0.5949724164706738,0.6590589880943298,0.6034714874557056
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,T,728,0.5117582678794861,0.614010989010989,0.5982455160173181,0.6492474675178528,0.6011554275378082
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,A,728,0.42107143998146057,0.4876373626373626,0.3042744149605441,0.7851645350456238,0.3562019133732601
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,V,728,0.3980769217014313,0.5439560439560439,0.4559201356747369,0.7165518999099731,0.4228907732362493
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,TA,728,0.42107143998146057,0.5934065934065934,0.559867581706166,0.6601358652114868,0.5680404827910764
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,TV,728,0.3980769217014313,0.6002747252747253,0.5842152460266312,0.6859722137451172,0.575453733717388
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,AV,728,0.3980769217014313,0.43131868131868134,0.4262759970983259,0.8031644821166992,0.35346199972803627
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||||
B5_mofe_mlp,2026,audio_vision_10,0.1,TAV,728,0.3980769217014313,0.5535714285714286,0.49118433140019535,0.7740562558174133,0.5279377438591082
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,learned_router,728,0.45884615384615385,0.6387362637362637,0.6013762119617033,0.6582632660865784,0.5998105774990818
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,T,728,0.45884615182876587,0.6098901098901099,0.5927342612347185,0.6530159711837769,0.5924213553262381
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,A,728,0.42030221223831177,0.4739010989010989,0.2799395224420051,0.8183923363685608,0.22552480747030987
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,V,728,0.3982967138290405,0.5123626373626373,0.41084897900937084,0.7401790618896484,0.34290184431076304
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,TA,728,0.42030221223831177,0.603021978021978,0.5636157256230538,0.6699337959289551,0.5545966180956201
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,TV,728,0.3982967138290405,0.5961538461538461,0.5817349795156427,0.7066670656204224,0.5633093560522575
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,AV,728,0.3982967138290405,0.36813186813186816,0.35589607464607464,0.8376190066337585,0.24289847097047093
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||||
B5_mofe_mlp,2026,all_modalities_10,0.1,TAV,728,0.3982967138290405,0.5288461538461539,0.46033318738535584,0.7966769933700562,0.5109216642892338
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||||
B5_mofe_mlp,2026,text_20,0.2,learned_router,728,0.5064560439560439,0.6277472527472527,0.579286730359655,0.6673612594604492,0.5829749639030503
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||||
B5_mofe_mlp,2026,text_20,0.2,T,728,0.4112088084220886,0.6167582417582418,0.5881921764479171,0.6567916870117188,0.5831459023434139
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||||
B5_mofe_mlp,2026,text_20,0.2,A,728,0.47049450874328613,0.47115384615384615,0.27465560798894134,0.8285160064697266,0.21743928273022034
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||||
B5_mofe_mlp,2026,text_20,0.2,V,728,0.44483518600463867,0.5096153846153846,0.4084128341513546,0.7475921511650085,0.31692232958876915
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||||
B5_mofe_mlp,2026,text_20,0.2,TA,728,0.3752472698688507,0.603021978021978,0.5486119524164519,0.6673292517662048,0.539250775649662
|
||||
B5_mofe_mlp,2026,text_20,0.2,TV,728,0.35461539030075073,0.6112637362637363,0.5843667494564081,0.689144492149353,0.544504109553622
|
||||
B5_mofe_mlp,2026,text_20,0.2,AV,728,0.44483518600463867,0.3585164835164835,0.3446302940469433,0.8487928509712219,0.2126482794308453
|
||||
B5_mofe_mlp,2026,text_20,0.2,TAV,728,0.35461539030075073,0.5425824175824175,0.46587133463364855,0.7634091377258301,0.48214188094638644
|
||||
B5_mofe_mlp,2026,audio_20,0.2,learned_router,728,0.5117582417582418,0.6304945054945055,0.5954536143668596,0.6568871736526489,0.6037191294218217
|
||||
B5_mofe_mlp,2026,audio_20,0.2,T,728,0.5117582678794861,0.614010989010989,0.5983472125624337,0.650320291519165,0.6009217628625136
|
||||
B5_mofe_mlp,2026,audio_20,0.2,A,728,0.3796977996826172,0.5164835164835165,0.3655881236095169,0.7692446112632751,0.3949788114535673
|
||||
B5_mofe_mlp,2026,audio_20,0.2,V,728,0.44483518600463867,0.5151098901098901,0.41620583054274807,0.7414965629577637,0.33444942065556305
|
||||
B5_mofe_mlp,2026,audio_20,0.2,TA,728,0.3796977996826172,0.5989010989010989,0.5638265304840163,0.6491042971611023,0.5770019410427926
|
||||
B5_mofe_mlp,2026,audio_20,0.2,TV,728,0.44483518600463867,0.592032967032967,0.5774181294613681,0.7061969041824341,0.5658046168061596
|
||||
B5_mofe_mlp,2026,audio_20,0.2,AV,728,0.35961538553237915,0.4793956043956044,0.4729905027892644,0.7711812257766724,0.3921269492204333
|
||||
B5_mofe_mlp,2026,audio_20,0.2,TAV,728,0.35961538553237915,0.5645604395604396,0.509050719882809,0.7490760684013367,0.5341345004529877
|
||||
B5_mofe_mlp,2026,vision_20,0.2,learned_router,728,0.5117582417582418,0.6277472527472527,0.5900160130008749,0.6632897853851318,0.6042444043430241
|
||||
B5_mofe_mlp,2026,vision_20,0.2,T,728,0.5117582678794861,0.6126373626373627,0.5965577523042379,0.6482207179069519,0.6014239127944337
|
||||
B5_mofe_mlp,2026,vision_20,0.2,A,728,0.47049450874328613,0.4725274725274725,0.2753954425047768,0.8218814730644226,0.23031725904419292
|
||||
B5_mofe_mlp,2026,vision_20,0.2,V,728,0.3572802245616913,0.5480769230769231,0.45491017561200736,0.7200025916099548,0.41887110693834134
|
||||
B5_mofe_mlp,2026,vision_20,0.2,TA,728,0.47049450874328613,0.592032967032967,0.5532162058371736,0.6667653918266296,0.5596752023907243
|
||||
B5_mofe_mlp,2026,vision_20,0.2,TV,728,0.3572802245616913,0.6085164835164835,0.5858009850150654,0.6767599582672119,0.5666763582603909
|
||||
B5_mofe_mlp,2026,vision_20,0.2,AV,728,0.3572802245616913,0.45604395604395603,0.45257735286592293,0.7822015881538391,0.3511756469807228
|
||||
B5_mofe_mlp,2026,vision_20,0.2,TAV,728,0.3572802245616913,0.5673076923076923,0.5113134010717539,0.7461904287338257,0.5258941828977346
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,learned_router,728,0.5117582417582418,0.625,0.5917418600128784,0.6548266410827637,0.6054018274439124
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,T,728,0.5117582678794861,0.614010989010989,0.5983472125624337,0.649300754070282,0.6012901186776531
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,A,728,0.37296703457832336,0.5041208791208791,0.35789310705995514,0.7596713900566101,0.41398276883225044
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,V,728,0.3531593382358551,0.5796703296703297,0.5048183867639185,0.6984941959381104,0.4714365413048334
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,TA,728,0.37296703457832336,0.5892857142857143,0.5573263153954385,0.6522572040557861,0.5764869722455894
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,TV,728,0.3531593382358551,0.6057692307692307,0.5884441789459711,0.6706872582435608,0.581897930872946
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,AV,728,0.3531593382358551,0.4684065934065934,0.465468176106474,0.767947793006897,0.41865978021168704
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,TAV,728,0.3531593382358551,0.5728021978021978,0.5181235721920635,0.7481652498245239,0.5424179636227278
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,learned_router,728,0.40585164835164833,0.6387362637362637,0.6023597229130889,0.6525924205780029,0.601538369275999
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,T,728,0.40585166215896606,0.6057692307692307,0.5895572046059541,0.6424159407615662,0.5987482734789812
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,A,728,0.3694780170917511,0.47802197802197804,0.2829329028964813,0.8103722333908081,0.25204782200960785
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,V,728,0.34881868958473206,0.5178571428571429,0.40966513694882706,0.7393192648887634,0.34226536554912906
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,TA,728,0.3694780170917511,0.5975274725274725,0.5569987222986782,0.6711844801902771,0.560237183016514
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,TV,728,0.34881868958473206,0.5906593406593407,0.5720218781867062,0.699638843536377,0.5616554801012917
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,AV,728,0.34881868958473206,0.37362637362637363,0.3626956690910179,0.8267216682434082,0.25176083351503564
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,TAV,728,0.34881868958473206,0.5453296703296703,0.4749388892268766,0.7958879470825195,0.5090043003952414
|
||||
B5_mofe_mlp,2026,text_30,0.3,learned_router,728,0.5032417582417582,0.6236263736263736,0.5695777746219127,0.6862288117408752,0.5485307360149316
|
||||
B5_mofe_mlp,2026,text_30,0.3,T,728,0.35857143998146057,0.6002747252747253,0.5650627890671912,0.6760544180870056,0.5486430119282898
|
||||
B5_mofe_mlp,2026,text_30,0.3,A,728,0.47049450874328613,0.4684065934065934,0.2694917313065056,0.8302391171455383,0.21220052810195741
|
||||
B5_mofe_mlp,2026,text_30,0.3,V,728,0.44483518600463867,0.5041208791208791,0.40060701323330045,0.7515881657600403,0.3084106819138643
|
||||
B5_mofe_mlp,2026,text_30,0.3,TA,728,0.32582417130470276,0.5824175824175825,0.5246945241369286,0.692663848400116,0.4910659178654774
|
||||
B5_mofe_mlp,2026,text_30,0.3,TV,728,0.3089011013507843,0.5934065934065934,0.5598344950469888,0.7086329460144043,0.49570851546354966
|
||||
B5_mofe_mlp,2026,text_30,0.3,AV,728,0.44483518600463867,0.35714285714285715,0.3435056224920738,0.8512967228889465,0.19852242746832857
|
||||
B5_mofe_mlp,2026,text_30,0.3,TAV,728,0.3089011013507843,0.5343406593406593,0.45069366576352604,0.7611382603645325,0.43668715634323624
|
||||
B5_mofe_mlp,2026,audio_30,0.3,learned_router,728,0.5117582417582418,0.6277472527472527,0.5928207016211315,0.6564014554023743,0.6057011879455848
|
||||
B5_mofe_mlp,2026,audio_30,0.3,T,728,0.5117582678794861,0.6126373626373627,0.5963454618716882,0.6506627798080444,0.6009406388191995
|
||||
B5_mofe_mlp,2026,audio_30,0.3,A,728,0.3250274658203125,0.521978021978022,0.38592081478406426,0.7444095611572266,0.43124762537966826
|
||||
B5_mofe_mlp,2026,audio_30,0.3,V,728,0.44483518600463867,0.5151098901098901,0.4189500868178652,0.7407843470573425,0.3353742329440497
|
||||
B5_mofe_mlp,2026,audio_30,0.3,TA,728,0.3250274658203125,0.6208791208791209,0.5886808752593625,0.6490352749824524,0.570975506988905
|
||||
B5_mofe_mlp,2026,audio_30,0.3,TV,728,0.44483518600463867,0.5892857142857143,0.5746190571714002,0.7062152624130249,0.5695050918318726
|
||||
B5_mofe_mlp,2026,audio_30,0.3,AV,728,0.3078022003173828,0.4876373626373626,0.4781988617789497,0.7588927745819092,0.41241611684819374
|
||||
B5_mofe_mlp,2026,audio_30,0.3,TAV,728,0.3078022003173828,0.5796703296703297,0.5254621943407217,0.7300676703453064,0.5331740156497008
|
||||
B5_mofe_mlp,2026,vision_30,0.3,learned_router,728,0.5117582417582418,0.6291208791208791,0.5902326768980343,0.6632499098777771,0.6060668473400238
|
||||
B5_mofe_mlp,2026,vision_30,0.3,T,728,0.5117582678794861,0.6112637362637363,0.5951956697149005,0.648055374622345,0.6013617900975071
|
||||
B5_mofe_mlp,2026,vision_30,0.3,A,728,0.47049450874328613,0.4725274725274725,0.2753954425047768,0.8200526237487793,0.2290184928714137
|
||||
B5_mofe_mlp,2026,vision_30,0.3,V,728,0.307609885931015,0.5714285714285714,0.480133525611997,0.6950517296791077,0.48955757399923455
|
||||
B5_mofe_mlp,2026,vision_30,0.3,TA,728,0.47049450874328613,0.592032967032967,0.5533383448560617,0.6673561334609985,0.5595820020363866
|
||||
B5_mofe_mlp,2026,vision_30,0.3,TV,728,0.307609885931015,0.6181318681318682,0.5942276325734972,0.6576289534568787,0.5825792146121718
|
||||
B5_mofe_mlp,2026,vision_30,0.3,AV,728,0.307609885931015,0.4835164835164835,0.4758194996023056,0.7574149966239929,0.39536644001209464
|
||||
B5_mofe_mlp,2026,vision_30,0.3,TAV,728,0.307609885931015,0.5851648351648352,0.5229046773276295,0.7180534601211548,0.542626958107565
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,learned_router,728,0.5117582417582418,0.625,0.5962838833608418,0.6554995775222778,0.6044590906471965
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,T,728,0.5117582678794861,0.6126373626373627,0.5966200968456806,0.6497842073440552,0.6010002684577302
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,A,728,0.3190384805202484,0.521978021978022,0.40390961057275176,0.7342812418937683,0.44376299869270686
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,V,728,0.301071435213089,0.5686813186813187,0.5040223473945638,0.687127411365509,0.4953386251138901
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,TA,728,0.3190384805202484,0.5906593406593407,0.5620402015554825,0.6461183428764343,0.5751739467292083
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,TV,728,0.301071435213089,0.6167582417582418,0.6003175316510284,0.6656390428543091,0.5833222854175106
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,AV,728,0.301071435213089,0.5,0.49814761477760233,0.7473122477531433,0.4398620166190232
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,TAV,728,0.301071435213089,0.5673076923076923,0.5181807136427148,0.7298097610473633,0.549260519080892
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,learned_router,728,0.36043956043956044,0.6167582417582418,0.5778458150682998,0.6775782108306885,0.5767908971520759
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,T,728,0.36043956875801086,0.603021978021978,0.582619604272029,0.6699808835983276,0.5730899311736721
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,A,728,0.32840660214424133,0.4725274725274725,0.28157868772104216,0.8073930144309998,0.2329322112177729
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,V,728,0.31060439348220825,0.5274725274725275,0.4283917020609205,0.7411948442459106,0.35155160333443614
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,TA,728,0.32840660214424133,0.5755494505494505,0.5352650821255436,0.6817681789398193,0.5363938930111966
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,TV,728,0.31060439348220825,0.5810439560439561,0.5628840082630775,0.7163251042366028,0.5509194266569809
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,AV,728,0.31060439348220825,0.3873626373626374,0.37820754147953356,0.8290948271751404,0.2590757927734446
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,TAV,728,0.31060439348220825,0.5343406593406593,0.46600788776303587,0.795678436756134,0.50343403287812
|
||||
|
@@ -0,0 +1,49 @@
|
||||
seed,condition,spearman_macro_f1_vs_mae,spearman_macro_f1_vs_pearson,best_macro_f1_expert,best_mae_expert,best_pearson_expert,macro_f1_order_best_to_worst,mae_order_best_to_worst,pearson_order_best_to_worst
|
||||
42,all_modalities_10,-0.9285714285714288,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,all_modalities_20,-0.8571428571428573,0.9285714285714288,TA,T,T,TA>T>TV>TAV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,all_modalities_30,-0.9285714285714288,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,audio_10,-0.8571428571428573,0.8571428571428573,T,T,T,T>TA>TV>TAV>V>AV>A,T>TA>TV>TAV>A>AV>V,T>TA>TAV>TV>AV>A>V
|
||||
42,audio_20,-0.9285714285714288,0.9285714285714288,TA,T,T,TA>T>TAV>TV>A>AV>V,T>TA>TV>TAV>A>AV>V,T>TA>TAV>TV>AV>A>V
|
||||
42,audio_30,-0.9285714285714288,0.9285714285714288,TA,T,T,TA>T>TAV>TV>A>AV>V,T>TA>TV>TAV>A>AV>V,T>TA>TAV>TV>AV>A>V
|
||||
42,audio_vision_10,-0.9285714285714288,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,audio_vision_20,-0.9285714285714288,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,audio_vision_30,-0.9642857142857145,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>AV>A,T>TA>TV>TAV>AV>V>A
|
||||
42,clean,-0.9285714285714288,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,text_10,-0.9642857142857145,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,text_20,-0.9642857142857145,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,text_30,-0.9642857142857145,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TA>TV>TAV>AV>V>A
|
||||
42,vision_10,-0.9642857142857145,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>AV>A,T>TA>TV>TAV>AV>V>A
|
||||
42,vision_20,-0.8928571428571429,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TV>TAV>TA>V>AV>A,T>TA>TV>TAV>AV>V>A
|
||||
42,vision_30,-0.8571428571428573,0.9642857142857145,T,T,T,T>TA>TAV>TV>V>AV>A,T>TV>TAV>TA>V>AV>A,T>TA>TV>TAV>V>AV>A
|
||||
2026,all_modalities_10,-0.8928571428571429,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
2026,all_modalities_20,-0.8928571428571429,0.9642857142857145,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>A>AV
|
||||
2026,all_modalities_30,-0.8928571428571429,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
2026,audio_10,-0.8928571428571429,0.9642857142857145,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
2026,audio_20,-0.7142857142857144,0.8571428571428573,T,TA,T,T>TV>TA>TAV>AV>V>A,TA>T>TV>V>TAV>A>AV,T>TA>TV>TAV>A>AV>V
|
||||
2026,audio_30,-0.8571428571428573,0.8928571428571429,T,TA,T,T>TA>TV>TAV>AV>V>A,TA>T>TV>TAV>V>A>AV,T>TA>TV>TAV>A>AV>V
|
||||
2026,audio_vision_10,-0.8928571428571429,0.9642857142857145,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>A>AV
|
||||
2026,audio_vision_20,-0.8928571428571429,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
2026,audio_vision_30,-0.7857142857142859,0.9285714285714288,TV,TA,T,TV>T>TA>TAV>V>AV>A,TA>T>TV>V>TAV>A>AV,T>TV>TA>TAV>V>A>AV
|
||||
2026,clean,-0.8928571428571429,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
2026,text_10,-0.8928571428571429,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
2026,text_20,-0.8928571428571429,0.9642857142857145,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>A>AV
|
||||
2026,text_30,-0.8928571428571429,0.9642857142857145,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>A>AV,T>TV>TA>TAV>V>A>AV
|
||||
2026,vision_10,-0.9285714285714288,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>AV>A,T>TV>TA>TAV>V>AV>A
|
||||
2026,vision_20,-0.9285714285714288,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>V>TAV>AV>A,T>TV>TA>TAV>V>AV>A
|
||||
2026,vision_30,-0.9642857142857145,1.0,T,T,T,T>TV>TA>TAV>V>AV>A,T>TV>TA>V>TAV>AV>A,T>TV>TA>TAV>V>AV>A
|
||||
3407,all_modalities_10,-0.9285714285714288,0.8571428571428573,T,T,T,T>TA>TAV>TV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,all_modalities_20,-0.8214285714285715,0.8571428571428573,T,T,T,T>TAV>TV>TA>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,all_modalities_30,-0.9285714285714288,0.9642857142857145,T,T,T,T>TV>TA>TAV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,audio_10,-0.8214285714285715,0.8928571428571429,T,T,T,T>TA>TAV>TV>AV>V>A,T>TA>TV>TAV>A>V>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,audio_20,-0.8214285714285715,0.9285714285714288,T,T,T,T>TA>TAV>TV>AV>V>A,T>TA>TV>TAV>A>V>AV,T>TA>TV>TAV>AV>A>V
|
||||
3407,audio_30,-0.7142857142857144,0.8571428571428573,TAV,T,T,TAV>TA>T>TV>AV>A>V,T>TA>TV>TAV>A>AV>V,T>TA>TAV>TV>AV>A>V
|
||||
3407,audio_vision_10,-0.9642857142857145,0.9642857142857145,T,T,T,T>TA>TV>TAV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
3407,audio_vision_20,-0.8214285714285715,0.8928571428571429,TV,T,T,TV>TA>T>TAV>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
3407,audio_vision_30,-0.8571428571428573,0.8214285714285715,TA,TA,T,TA>TAV>T>TV>V>AV>A,TA>T>TV>TAV>V>A>AV,T>TA>TV>TAV>V>AV>A
|
||||
3407,clean,-0.8214285714285715,0.8571428571428573,T,T,T,T>TAV>TV>TA>V>AV>A,T>TA>TV>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,text_10,-0.8571428571428573,0.8571428571428573,T,T,T,T>TA>TAV>TV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,text_20,-0.8214285714285715,0.8214285714285715,T,T,T,T>TAV>TA>TV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,text_30,-0.8571428571428573,0.8571428571428573,T,T,T,T>TA>TAV>TV>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TV>TA>TAV>AV>V>A
|
||||
3407,vision_10,-0.8571428571428573,0.8928571428571429,T,T,T,T>TAV>TV>TA>V>AV>A,T>TV>TA>TAV>V>A>AV,T>TV>TA>TAV>V>AV>A
|
||||
3407,vision_20,-0.7857142857142859,0.7857142857142859,TAV,T,T,TAV>T>TV>TA>V>AV>A,T>TV>TA>TAV>V>AV>A,T>TV>TA>TAV>V>AV>A
|
||||
3407,vision_30,-0.8928571428571429,0.8571428571428573,T,T,T,T>TAV>TA>TV>V>AV>A,T>TA>TV>TAV>V>AV>A,T>TV>TA>TAV>V>AV>A
|
||||
|
@@ -0,0 +1,41 @@
|
||||
{
|
||||
"diagnostic": "forced-expert task preference for the retained single-router MoFE-7",
|
||||
"checkpoint_dir": "/home/gloamxun/modeling_zhaocui/deep_learning/Q2/outputs/mofe_7experts/models/B5_mofe_mlp",
|
||||
"checkpoint_seeds": [
|
||||
42,
|
||||
3407,
|
||||
2026
|
||||
],
|
||||
"feature_file": "/home/gloamxun/modeling_zhaocui/E题数据/附件2-数据集特征文件/aligned_50.pkl",
|
||||
"scaler_file": "/home/gloamxun/modeling_zhaocui/deep_learning/Q2/outputs/mofe_7experts/aligned_robust_stats.npz",
|
||||
"scaler_sha256": "3b62802bef92f49a7846773741bc57fda1564aa9eed43f047a3e31a9c357c4e8",
|
||||
"device": "cuda",
|
||||
"conditions": [
|
||||
"clean",
|
||||
"text_10",
|
||||
"audio_10",
|
||||
"vision_10",
|
||||
"audio_vision_10",
|
||||
"all_modalities_10",
|
||||
"text_20",
|
||||
"audio_20",
|
||||
"vision_20",
|
||||
"audio_vision_20",
|
||||
"all_modalities_20",
|
||||
"text_30",
|
||||
"audio_30",
|
||||
"vision_30",
|
||||
"audio_vision_30",
|
||||
"all_modalities_30"
|
||||
],
|
||||
"forced_expert_policy": "use the requested expert where its modality subset is available; fall back to the trained single router at positions where it is unavailable; all-missing positions use the learned missing token",
|
||||
"scope_note": "50 official ordered wordpiece positions; no claim about physical-time reliability",
|
||||
"interpretation_note": "Ranking agreement is descriptive on the supplied validation split; it is a motivation diagnostic, not an unbiased test-set estimate.",
|
||||
"feature_sha256": "66e867aa74bc70a844e806e5571e371c9abb4a35f9e2887ce9b4d97ff2cb8fcd",
|
||||
"cuda_device": "NVIDIA GeForce RTX 5070 Ti",
|
||||
"python_version": "3.14.7 (main, Aug 10 2026, 00:00:00) [GCC 16.1.1 20260515 (Red Hat 16.1.1-2)]",
|
||||
"torch_version": "2.14.0+cu130",
|
||||
"numpy_version": "2.5.3",
|
||||
"valid_examples": 728,
|
||||
"corruption_seed_protocol": "seed + 13 + pattern_index*101 + int(rate*1000)"
|
||||
}
|
||||
@@ -0,0 +1,47 @@
|
||||
# Single-router MoFE 任务偏好诊断
|
||||
|
||||
本诊断使用保留的 single-router 检查点和验证集，用于判断是否值得增加第二个 router；它不是测试集估计。
|
||||
|
||||
## Forced-expert 规则
|
||||
|
||||
所选模态子集可用的位置强制使用对应 expert；该子集不可用时，由已训练 router 在其他可用 expert 中选择；全模态缺失时沿用 learned missing token。可用率表示所选 expert 能被强制使用的位置比例。
|
||||
|
||||
## 缺失条件平均指标
|
||||
|
||||
下表先在每个 seed 内对 15 种连续块缺失条件求平均，再汇总三个 seed；seed 标准差见 CSV。
|
||||
|
||||
| Expert | Macro-F1 ↑ | MAE ↓ | Pearson ↑ | 可强制使用比例 |
|
||||
| --- | ---: | ---: | ---: | ---: |
|
||||
| T | 0.590 | 0.643 | 0.606 | 0.471 |
|
||||
| A | 0.318 | 0.779 | 0.252 | 0.412 |
|
||||
| V | 0.429 | 0.747 | 0.340 | 0.390 |
|
||||
| TA | 0.567 | 0.659 | 0.577 | 0.393 |
|
||||
| TV | 0.561 | 0.667 | 0.567 | 0.372 |
|
||||
| AV | 0.393 | 0.799 | 0.349 | 0.372 |
|
||||
| TAV | 0.531 | 0.708 | 0.542 | 0.354 |
|
||||
| learned_router | 0.600 | 0.641 | 0.605 | 0.490 |
|
||||
|
||||
## 两个任务的 expert 偏好
|
||||
|
||||
在 48 个 seed—条件组合中，分类 Macro-F1 与回归 MAE 的平均 Spearman ρ 为 **-0.885**。MAE 越低越好，因此负相关表示两个指标倾向于选中相似的 expert。Macro-F1 与 Pearson 的平均 ρ 为 **0.931**。
|
||||
|
||||
六个重点条件下的相关性先按三个 seed 求平均；最优 expert 一栏显示三个 seed 中的多数结果：
|
||||
|
||||
| 条件 | ρ(Macro-F1, MAE) | ρ(Macro-F1, Pearson) | Macro-F1 最优 | MAE 最优 | Pearson 最优 |
|
||||
| --- | ---: | ---: | --- | --- | --- |
|
||||
| Clean | -0.881 | 0.940 | T (3/3) | T (3/3) | T (3/3) |
|
||||
| Text 30% | -0.905 | 0.929 | T (3/3) | T (3/3) | T (3/3) |
|
||||
| Audio 30% | -0.833 | 0.893 | T (1/3), TA (1/3), TAV (1/3) | T (2/3) | T (3/3) |
|
||||
| Vision 30% | -0.905 | 0.940 | T (3/3) | T (3/3) | T (3/3) |
|
||||
| Audio+Vision 30% | -0.869 | 0.905 | T (1/3), TA (1/3), TV (1/3) | TA (2/3) | T (3/3) |
|
||||
| All-modal 30% | -0.917 | 0.976 | T (3/3) | T (3/3) | T (3/3) |
|
||||
|
||||
各指标的最优 expert 次数：Macro-F1（T: 40, A: 0, V: 0, TA: 4, TV: 2, AV: 0, TAV: 2）；MAE（T: 44, A: 0, V: 0, TA: 4, TV: 0, AV: 0, TAV: 0）；Pearson（T: 48, A: 0, V: 0, TA: 0, TV: 0, AV: 0, TAV: 0）。
|
||||
|
||||
当前排名没有显示稳定的分类—回归 expert 分工：Macro-F1 较高通常同时对应较低 MAE 和较高 Pearson；文本 expert 在分类与回归指标上都是最常见的赢家。因此，这项诊断**没有提供增加第二个 router 所需的任务特异模态偏好证据**。目前保留 single-router 作为活动参照；这不代表两个任务在任何数据或设置下都不可能需要不同路由。
|
||||
|
||||
## 结论范围
|
||||
|
||||
输入是官方提供的 50 个有序 wordpiece 位置。结果只反映这些位置及本次缺失掩码下的任务与 expert 关系，不表示物理时间可靠性。
|
||||
|
||||
逐条件结果见 `forced_expert_metrics.csv` 和 `rank_concordance.csv`；跨 seed 汇总见 `expert_task_preference_summary.csv`。
|
||||
+337
@@ -0,0 +1,337 @@
|
||||
method,seed,condition,expert,available_position_fraction,accuracy,macro_f1,mae,pearson
|
||||
B5_mofe_mlp,42,clean,T,0.5117582417582418,0.6304945054945055,0.595530036337148,0.6439222097396851,0.6129420612443442
|
||||
B5_mofe_mlp,42,clean,A,0.4704945054945055,0.47527472527472525,0.298145070470697,0.7733861207962036,0.18784968852824
|
||||
B5_mofe_mlp,42,clean,V,0.44483516483516483,0.5027472527472527,0.40175895555984303,0.766243577003479,0.24655657337265044
|
||||
B5_mofe_mlp,42,clean,TA,0.4704945054945055,0.6126373626373627,0.5778441259738553,0.6754669547080994,0.5976613672709937
|
||||
B5_mofe_mlp,42,clean,TV,0.44483516483516483,0.5659340659340659,0.5313464424314036,0.6711714863777161,0.5439695555081324
|
||||
B5_mofe_mlp,42,clean,AV,0.44483516483516483,0.39972527472527475,0.32010564554339865,0.8058619499206543,0.2853473823193152
|
||||
B5_mofe_mlp,42,clean,TAV,0.44483516483516483,0.5192307692307693,0.5075932022075595,0.7201082110404968,0.5295944326442668
|
||||
B5_mofe_mlp,42,text_10,T,0.46244505494505495,0.625,0.586687579750888,0.6396908164024353,0.6069353393592744
|
||||
B5_mofe_mlp,42,text_10,A,0.4704945054945055,0.4725274725274725,0.29847247595086945,0.7734847068786621,0.1872761811347766
|
||||
B5_mofe_mlp,42,text_10,V,0.44483516483516483,0.5013736263736264,0.40093402112196824,0.7681402564048767,0.23859029167275192
|
||||
B5_mofe_mlp,42,text_10,TA,0.4237362637362637,0.6043956043956044,0.5640906610207688,0.6682833433151245,0.590374645148395
|
||||
B5_mofe_mlp,42,text_10,TV,0.4011813186813187,0.5590659340659341,0.5191159133025295,0.6736815571784973,0.5364919274641561
|
||||
B5_mofe_mlp,42,text_10,AV,0.44483516483516483,0.39697802197802196,0.31798635878496145,0.8078023195266724,0.2802269980427409
|
||||
B5_mofe_mlp,42,text_10,TAV,0.4011813186813187,0.5233516483516484,0.5067270736643431,0.7274370193481445,0.5169178278994004
|
||||
B5_mofe_mlp,42,audio_10,T,0.5117582417582418,0.6291208791208791,0.5945275158931668,0.642977774143219,0.613275492732102
|
||||
B5_mofe_mlp,42,audio_10,A,0.4218681318681319,0.5206043956043956,0.3800213409408812,0.7459056973457336,0.3452087882296117
|
||||
B5_mofe_mlp,42,audio_10,V,0.44483516483516483,0.5027472527472527,0.40304222030887615,0.7655854225158691,0.2472652676368147
|
||||
B5_mofe_mlp,42,audio_10,TA,0.4218681318681319,0.6208791208791209,0.5887443905119517,0.6653785109519958,0.6021205001293886
|
||||
B5_mofe_mlp,42,audio_10,TV,0.44483516483516483,0.5645604395604396,0.5312885900336469,0.6704310178756714,0.5439517055201103
|
||||
B5_mofe_mlp,42,audio_10,AV,0.39903846153846156,0.4642857142857143,0.3849597770559165,0.7626285552978516,0.395749971509581
|
||||
B5_mofe_mlp,42,audio_10,TAV,0.39903846153846156,0.5343406593406593,0.5227392208880216,0.6968365907669067,0.5554522946329644
|
||||
B5_mofe_mlp,42,vision_10,T,0.5117582417582418,0.6291208791208791,0.5943509173547352,0.6446217894554138,0.6129818568677179
|
||||
B5_mofe_mlp,42,vision_10,A,0.4704945054945055,0.4766483516483517,0.2989428209119208,0.7728794813156128,0.18769972077258862
|
||||
B5_mofe_mlp,42,vision_10,V,0.39766483516483514,0.521978021978022,0.43087711258901057,0.7396351099014282,0.3554675683918263
|
||||
B5_mofe_mlp,42,vision_10,TA,0.4704945054945055,0.6098901098901099,0.5742147768264858,0.6766067743301392,0.5972162914035549
|
||||
B5_mofe_mlp,42,vision_10,TV,0.39766483516483514,0.5865384615384616,0.55296383612865,0.6538858413696289,0.5634815784773998
|
||||
B5_mofe_mlp,42,vision_10,AV,0.39766483516483514,0.4697802197802198,0.3822322738135533,0.7551643252372742,0.38427665028451974
|
||||
B5_mofe_mlp,42,vision_10,TAV,0.39766483516483514,0.5494505494505495,0.5360678828855083,0.6838967204093933,0.5509730603354713
|
||||
B5_mofe_mlp,42,audio_vision_10,T,0.5117582417582418,0.6304945054945055,0.5962642544403453,0.6440325975418091,0.6128134692505169
|
||||
B5_mofe_mlp,42,audio_vision_10,A,0.421978021978022,0.5123626373626373,0.3684800611034152,0.7456803917884827,0.33199118394826943
|
||||
B5_mofe_mlp,42,audio_vision_10,V,0.3991758241758242,0.5288461538461539,0.4393232991026214,0.7295649647712708,0.3589533434031505
|
||||
B5_mofe_mlp,42,audio_vision_10,TA,0.421978021978022,0.6071428571428571,0.5708085735541816,0.6724270582199097,0.6024973312871745
|
||||
B5_mofe_mlp,42,audio_vision_10,TV,0.3991758241758242,0.5824175824175825,0.5450890570908877,0.652445375919342,0.5628683926779028
|
||||
B5_mofe_mlp,42,audio_vision_10,AV,0.3991758241758242,0.4807692307692308,0.3902098705265415,0.7563263773918152,0.3809814529152993
|
||||
B5_mofe_mlp,42,audio_vision_10,TAV,0.3991758241758242,0.5508241758241759,0.5380789099976825,0.6938034892082214,0.5469244359251345
|
||||
B5_mofe_mlp,42,all_modalities_10,T,0.4626098901098901,0.6236263736263736,0.5896180574655738,0.644334077835083,0.6061671603432021
|
||||
B5_mofe_mlp,42,all_modalities_10,A,0.4235989010989011,0.47802197802197804,0.29851508448322833,0.7703589200973511,0.19932721022116437
|
||||
B5_mofe_mlp,42,all_modalities_10,V,0.4010164835164835,0.5096153846153846,0.40743192506208387,0.7642088532447815,0.2536261885599537
|
||||
B5_mofe_mlp,42,all_modalities_10,TA,0.4235989010989011,0.6071428571428571,0.5695040612711005,0.6758896708488464,0.5936468866005145
|
||||
B5_mofe_mlp,42,all_modalities_10,TV,0.4010164835164835,0.5769230769230769,0.5415381488196198,0.6721597909927368,0.5447657707430857
|
||||
B5_mofe_mlp,42,all_modalities_10,AV,0.4010164835164835,0.4024725274725275,0.3202895136648401,0.8006964921951294,0.28858268928350844
|
||||
B5_mofe_mlp,42,all_modalities_10,TAV,0.4010164835164835,0.5192307692307693,0.5060589429054257,0.7209683060646057,0.5279374148247811
|
||||
B5_mofe_mlp,42,text_20,T,0.4137362637362637,0.6277472527472527,0.5834715774578197,0.6387249827384949,0.595955769366048
|
||||
B5_mofe_mlp,42,text_20,A,0.4704945054945055,0.47115384615384615,0.2975569493673755,0.7751386761665344,0.17787620014502312
|
||||
B5_mofe_mlp,42,text_20,V,0.44483516483516483,0.49313186813186816,0.3957467065496128,0.7714186310768127,0.22587158419370937
|
||||
B5_mofe_mlp,42,text_20,TA,0.3776923076923077,0.6043956043956044,0.5611937927949194,0.6714186668395996,0.5678669912027287
|
||||
B5_mofe_mlp,42,text_20,TV,0.3565384615384615,0.5686813186813187,0.5239313100098085,0.681026816368103,0.5269364291198027
|
||||
B5_mofe_mlp,42,text_20,AV,0.44483516483516483,0.39972527472527475,0.31990146004230513,0.8130425810813904,0.2707806455648105
|
||||
B5_mofe_mlp,42,text_20,TAV,0.3565384615384615,0.5192307692307693,0.49528792280719197,0.7405415773391724,0.5088571803296038
|
||||
B5_mofe_mlp,42,audio_20,T,0.5117582417582418,0.6277472527472527,0.5934285449238298,0.6425583362579346,0.61296028794768
|
||||
B5_mofe_mlp,42,audio_20,A,0.3777747252747253,0.5370879120879121,0.4088556651206101,0.721038818359375,0.4088036003378612
|
||||
B5_mofe_mlp,42,audio_20,V,0.44483516483516483,0.5027472527472527,0.4043940692076286,0.766434907913208,0.2463825958649145
|
||||
B5_mofe_mlp,42,audio_20,TA,0.3777747252747253,0.6291208791208791,0.5983548479511946,0.6565340757369995,0.6034849351932553
|
||||
B5_mofe_mlp,42,audio_20,TV,0.44483516483516483,0.5618131868131868,0.5278821116181079,0.6707059144973755,0.5439704154498037
|
||||
B5_mofe_mlp,42,audio_20,AV,0.356978021978022,0.49175824175824173,0.4044220197597692,0.7304497957229614,0.46939736345936744
|
||||
B5_mofe_mlp,42,audio_20,TAV,0.356978021978022,0.554945054945055,0.5389342277853322,0.6833800673484802,0.5631089758912269
|
||||
B5_mofe_mlp,42,vision_20,T,0.5117582417582418,0.6304945054945055,0.595665938533476,0.645626425743103,0.6129211456979007
|
||||
B5_mofe_mlp,42,vision_20,A,0.4704945054945055,0.4739010989010989,0.294076640863259,0.772672712802887,0.1917203096512453
|
||||
B5_mofe_mlp,42,vision_20,V,0.3548901098901099,0.5494505494505495,0.4673960507937731,0.7191774845123291,0.4004458766947187
|
||||
B5_mofe_mlp,42,vision_20,TA,0.4704945054945055,0.6071428571428571,0.5708690749466393,0.6775083541870117,0.5974902403406877
|
||||
B5_mofe_mlp,42,vision_20,TV,0.3548901098901099,0.6016483516483516,0.5649164229707409,0.647191047668457,0.5713132358596449
|
||||
B5_mofe_mlp,42,vision_20,AV,0.3548901098901099,0.5137362637362637,0.43167042702402014,0.7291663289070129,0.41618639794585793
|
||||
B5_mofe_mlp,42,vision_20,TAV,0.3548901098901099,0.5741758241758241,0.5579426783722908,0.6710066199302673,0.5582889096221613
|
||||
B5_mofe_mlp,42,audio_vision_20,T,0.5117582417582418,0.6291208791208791,0.5952612725131757,0.6444123387336731,0.612903588247494
|
||||
B5_mofe_mlp,42,audio_vision_20,A,0.37423076923076926,0.5288461538461539,0.393885105990035,0.7293429374694824,0.3882759036052619
|
||||
B5_mofe_mlp,42,audio_vision_20,V,0.3539285714285714,0.5494505494505495,0.4675111779446084,0.7149078249931335,0.41871280252003096
|
||||
B5_mofe_mlp,42,audio_vision_20,TA,0.37423076923076926,0.6195054945054945,0.5844559446078783,0.669805645942688,0.6008561243242124
|
||||
B5_mofe_mlp,42,audio_vision_20,TV,0.3539285714285714,0.5892857142857143,0.5537996616712025,0.6531057953834534,0.5563709108545314
|
||||
B5_mofe_mlp,42,audio_vision_20,AV,0.3539285714285714,0.4945054945054945,0.4048075528799828,0.7323312163352966,0.42436332585578096
|
||||
B5_mofe_mlp,42,audio_vision_20,TAV,0.3539285714285714,0.5535714285714286,0.5374035508293326,0.6750969290733337,0.5556165429960925
|
||||
B5_mofe_mlp,42,all_modalities_20,T,0.41145604395604396,0.6112637362637363,0.5753999256800798,0.6470812559127808,0.6110403126351307
|
||||
B5_mofe_mlp,42,all_modalities_20,A,0.37502747252747254,0.48214285714285715,0.30971805746653613,0.7708897590637207,0.1984384514917167
|
||||
B5_mofe_mlp,42,all_modalities_20,V,0.35456043956043953,0.5,0.40444384179778897,0.768601655960083,0.24785317295609371
|
||||
B5_mofe_mlp,42,all_modalities_20,TA,0.37502747252747254,0.6126373626373627,0.581822149187397,0.6791433095932007,0.5855706598675895
|
||||
B5_mofe_mlp,42,all_modalities_20,TV,0.35456043956043953,0.5714285714285714,0.5350638931866368,0.6752636432647705,0.539181947101854
|
||||
B5_mofe_mlp,42,all_modalities_20,AV,0.35456043956043953,0.4065934065934066,0.33361946481005195,0.7985524535179138,0.28911162438768584
|
||||
B5_mofe_mlp,42,all_modalities_20,TAV,0.35456043956043953,0.5137362637362637,0.5016717439879469,0.723558783531189,0.522880930319737
|
||||
B5_mofe_mlp,42,text_30,T,0.36975274725274726,0.6002747252747253,0.5489214966247952,0.6610613465309143,0.5660732620520418
|
||||
B5_mofe_mlp,42,text_30,A,0.4704945054945055,0.4739010989010989,0.29743008078567407,0.7761889696121216,0.1678484467957318
|
||||
B5_mofe_mlp,42,text_30,V,0.44483516483516483,0.489010989010989,0.3906705384925391,0.7730352282524109,0.21533832545300696
|
||||
B5_mofe_mlp,42,text_30,TA,0.3367857142857143,0.5769230769230769,0.5309590282919976,0.6845227479934692,0.5380880477965313
|
||||
B5_mofe_mlp,42,text_30,TV,0.31706043956043956,0.5563186813186813,0.5074245114833101,0.6991908550262451,0.5079541484193177
|
||||
B5_mofe_mlp,42,text_30,AV,0.44483516483516483,0.38873626373626374,0.3106438181055198,0.8153451681137085,0.25647904474699446
|
||||
B5_mofe_mlp,42,text_30,TAV,0.31706043956043956,0.510989010989011,0.48202998092174165,0.7513630390167236,0.4807588760950029
|
||||
B5_mofe_mlp,42,audio_30,T,0.5117582417582418,0.6304945054945055,0.5962642544403453,0.6413891911506653,0.6140593651176108
|
||||
B5_mofe_mlp,42,audio_30,A,0.3262087912087912,0.5480769230769231,0.4494048835498772,0.7181517481803894,0.4130354529119704
|
||||
B5_mofe_mlp,42,audio_30,V,0.44483516483516483,0.5027472527472527,0.40552179812400446,0.7659019231796265,0.24744831420819957
|
||||
B5_mofe_mlp,42,audio_30,TA,0.3262087912087912,0.6291208791208791,0.5964728532922603,0.6501736640930176,0.6030689771166702
|
||||
B5_mofe_mlp,42,audio_30,TV,0.44483516483516483,0.5618131868131868,0.5278372031251927,0.6705803871154785,0.5438638322507882
|
||||
B5_mofe_mlp,42,audio_30,AV,0.3069230769230769,0.49862637362637363,0.42544608223551644,0.7236812114715576,0.45260841133749147
|
||||
B5_mofe_mlp,42,audio_30,TAV,0.3069230769230769,0.5673076923076923,0.5511576680296482,0.6794567704200745,0.5516787374683813
|
||||
B5_mofe_mlp,42,vision_30,T,0.5117582417582418,0.6263736263736264,0.59178963181016,0.6464172601699829,0.6124405738784353
|
||||
B5_mofe_mlp,42,vision_30,A,0.4704945054945055,0.47527472527472525,0.29307320983548674,0.7725724577903748,0.18981334780850148
|
||||
B5_mofe_mlp,42,vision_30,V,0.3138186813186813,0.5480769230769231,0.46141777713440435,0.7053897380828857,0.4504351822566667
|
||||
B5_mofe_mlp,42,vision_30,TA,0.4704945054945055,0.6112637362637363,0.5755727285311548,0.6785207986831665,0.5965959233259053
|
||||
B5_mofe_mlp,42,vision_30,TV,0.3138186813186813,0.5947802197802198,0.5518425273811883,0.6574218273162842,0.5668784431581148
|
||||
B5_mofe_mlp,42,vision_30,AV,0.3138186813186813,0.5027472527472527,0.413102983693412,0.7221376299858093,0.4423578428565793
|
||||
B5_mofe_mlp,42,vision_30,TAV,0.3138186813186813,0.5810439560439561,0.5627987997604266,0.6714197397232056,0.5504939616109109
|
||||
B5_mofe_mlp,42,audio_vision_30,T,0.5117582417582418,0.6291208791208791,0.5956657591699687,0.6447409987449646,0.6124815887059187
|
||||
B5_mofe_mlp,42,audio_vision_30,A,0.32593406593406593,0.5412087912087912,0.4293427018964002,0.7119898796081543,0.4611692059662869
|
||||
B5_mofe_mlp,42,audio_vision_30,V,0.308489010989011,0.5741758241758241,0.5081685315054737,0.7036085724830627,0.46865245226218855
|
||||
B5_mofe_mlp,42,audio_vision_30,TA,0.32593406593406593,0.6167582417582418,0.5796313859552673,0.6652615666389465,0.6066108477643619
|
||||
B5_mofe_mlp,42,audio_vision_30,TV,0.308489010989011,0.6085164835164835,0.5747678972005031,0.6532444953918457,0.5685188687826935
|
||||
B5_mofe_mlp,42,audio_vision_30,AV,0.308489010989011,0.5178571428571429,0.4479560935960237,0.704010009765625,0.473760873249426
|
||||
B5_mofe_mlp,42,audio_vision_30,TAV,0.308489010989011,0.5769230769230769,0.5590219753958139,0.6671830415725708,0.5613400189071075
|
||||
B5_mofe_mlp,42,all_modalities_30,T,0.3595054945054945,0.6332417582417582,0.5994013685816965,0.642018735408783,0.6142476754248422
|
||||
B5_mofe_mlp,42,all_modalities_30,A,0.32604395604395603,0.4876373626373626,0.32114976052878363,0.7629672288894653,0.24577614371604897
|
||||
B5_mofe_mlp,42,all_modalities_30,V,0.30766483516483517,0.5137362637362637,0.41564992061683226,0.7619248032569885,0.2628075288162841
|
||||
B5_mofe_mlp,42,all_modalities_30,TA,0.32604395604395603,0.6277472527472527,0.5901208902602798,0.6717713475227356,0.6055638351449961
|
||||
B5_mofe_mlp,42,all_modalities_30,TV,0.30766483516483517,0.5851648351648352,0.550384612243989,0.6579669713973999,0.5550816637819891
|
||||
B5_mofe_mlp,42,all_modalities_30,AV,0.30766483516483517,0.43131868131868134,0.3524060719327709,0.7886311411857605,0.2950171215037075
|
||||
B5_mofe_mlp,42,all_modalities_30,TAV,0.30766483516483517,0.5206043956043956,0.5084554432330729,0.7108278274536133,0.5347221240292945
|
||||
B5_mofe_mlp,3407,clean,T,0.5117582417582418,0.6002747252747253,0.589715106019248,0.6271728873252869,0.6222406977786201
|
||||
B5_mofe_mlp,3407,clean,A,0.4704945054945055,0.46703296703296704,0.25617731189594245,0.8055213093757629,0.08527244746812068
|
||||
B5_mofe_mlp,3407,clean,V,0.44483516483516483,0.45879120879120877,0.3911083700819353,0.7868512272834778,0.27334952956888975
|
||||
B5_mofe_mlp,3407,clean,TA,0.4704945054945055,0.5796703296703297,0.5637105051146315,0.6420981884002686,0.5835249053178219
|
||||
B5_mofe_mlp,3407,clean,TV,0.44483516483516483,0.6153846153846154,0.5641846149831432,0.6430085301399231,0.5929148218414205
|
||||
B5_mofe_mlp,3407,clean,AV,0.44483516483516483,0.3791208791208791,0.31403029968176926,0.8854933381080627,0.2789162730797137
|
||||
B5_mofe_mlp,3407,clean,TAV,0.44483516483516483,0.5879120879120879,0.5681219195313041,0.6709685921669006,0.5645502116442188
|
||||
B5_mofe_mlp,3407,text_10,T,0.46123626373626375,0.614010989010989,0.5962559055831377,0.6278678774833679,0.617857871648632
|
||||
B5_mofe_mlp,3407,text_10,A,0.4704945054945055,0.4642857142857143,0.24969978803929094,0.8068049550056458,0.08051328125107551
|
||||
B5_mofe_mlp,3407,text_10,V,0.44483516483516483,0.4574175824175824,0.3878406396990897,0.7909942269325256,0.26236773636559957
|
||||
B5_mofe_mlp,3407,text_10,TA,0.42271978021978024,0.5879120879120879,0.5646643159293967,0.6490334868431091,0.5744751061732449
|
||||
B5_mofe_mlp,3407,text_10,TV,0.39942307692307694,0.6085164835164835,0.5474885374714241,0.6448302268981934,0.5895230158639547
|
||||
B5_mofe_mlp,3407,text_10,AV,0.44483516483516483,0.37774725274725274,0.3110187465790914,0.8889136910438538,0.2696459968528376
|
||||
B5_mofe_mlp,3407,text_10,TAV,0.39942307692307694,0.5934065934065934,0.563693177045021,0.6679768562316895,0.5622421334799538
|
||||
B5_mofe_mlp,3407,audio_10,T,0.5117582417582418,0.5989010989010989,0.5878169018954168,0.6271204948425293,0.6223836004743148
|
||||
B5_mofe_mlp,3407,audio_10,A,0.4228021978021978,0.5027472527472527,0.332656408166132,0.7686276435852051,0.2539853638071684
|
||||
B5_mofe_mlp,3407,audio_10,V,0.44483516483516483,0.45604395604395603,0.38920601362461826,0.7875473499298096,0.27266225636799185
|
||||
B5_mofe_mlp,3407,audio_10,TA,0.4228021978021978,0.5947802197802198,0.5806242036699651,0.6359114050865173,0.5923569096429423
|
||||
B5_mofe_mlp,3407,audio_10,TV,0.44483516483516483,0.6167582417582418,0.5663217661957952,0.6429393887519836,0.5927651982092371
|
||||
B5_mofe_mlp,3407,audio_10,AV,0.3992857142857143,0.44505494505494503,0.40079404466501245,0.8398518562316895,0.37350790006416895
|
||||
B5_mofe_mlp,3407,audio_10,TAV,0.3992857142857143,0.5879120879120879,0.5677938460265421,0.6635177135467529,0.5747748813576409
|
||||
B5_mofe_mlp,3407,vision_10,T,0.5117582417582418,0.5989010989010989,0.5881686695855791,0.6271764636039734,0.6224112877034929
|
||||
B5_mofe_mlp,3407,vision_10,A,0.4704945054945055,0.4697802197802198,0.2617495652772756,0.8053902387619019,0.08562714494931029
|
||||
B5_mofe_mlp,3407,vision_10,V,0.39975274725274723,0.5164835164835165,0.4530382033974704,0.7460650205612183,0.3701696777824128
|
||||
B5_mofe_mlp,3407,vision_10,TA,0.4704945054945055,0.5810439560439561,0.5652874494272252,0.6420679688453674,0.5835241403957903
|
||||
B5_mofe_mlp,3407,vision_10,TV,0.39975274725274723,0.6208791208791209,0.5716893090185614,0.6368684768676758,0.5996522472016457
|
||||
B5_mofe_mlp,3407,vision_10,AV,0.39975274725274723,0.4340659340659341,0.3798771393241414,0.8302299380302429,0.366026727245457
|
||||
B5_mofe_mlp,3407,vision_10,TAV,0.39975274725274723,0.5975274725274725,0.5773266951804078,0.6591137051582336,0.573922934425617
|
||||
B5_mofe_mlp,3407,audio_vision_10,T,0.5117582417582418,0.6002747252747253,0.5895426241854899,0.6275323629379272,0.6220930974326538
|
||||
B5_mofe_mlp,3407,audio_vision_10,A,0.421978021978022,0.4793956043956044,0.2964038513186514,0.7789896726608276,0.2398897695596731
|
||||
B5_mofe_mlp,3407,audio_vision_10,V,0.3987912087912088,0.4945054945054945,0.44061682531723784,0.7518566846847534,0.38529247892112506
|
||||
B5_mofe_mlp,3407,audio_vision_10,TA,0.421978021978022,0.5906593406593407,0.5759372217914477,0.6386086344718933,0.5889149782654084
|
||||
B5_mofe_mlp,3407,audio_vision_10,TV,0.3987912087912088,0.6195054945054945,0.5730831708901883,0.6402207016944885,0.5971608635562845
|
||||
B5_mofe_mlp,3407,audio_vision_10,AV,0.3987912087912088,0.4409340659340659,0.39365944462354036,0.8360045552253723,0.37457825919086657
|
||||
B5_mofe_mlp,3407,audio_vision_10,TAV,0.3987912087912088,0.5879120879120879,0.5702051410805352,0.6638661623001099,0.5713070790736874
|
||||
B5_mofe_mlp,3407,all_modalities_10,T,0.4610164835164835,0.5934065934065934,0.5840003133946626,0.63011234998703,0.6190678344486067
|
||||
B5_mofe_mlp,3407,all_modalities_10,A,0.4225274725274725,0.47115384615384615,0.2646409174971828,0.8042468428611755,0.08459595129973409
|
||||
B5_mofe_mlp,3407,all_modalities_10,V,0.39947802197802196,0.46016483516483514,0.39465376804402846,0.7862517237663269,0.2773313002639839
|
||||
B5_mofe_mlp,3407,all_modalities_10,TA,0.4225274725274725,0.5824175824175825,0.5671818574180514,0.6445116400718689,0.5822325816333559
|
||||
B5_mofe_mlp,3407,all_modalities_10,TV,0.39947802197802196,0.6043956043956044,0.5508070001152509,0.6478140354156494,0.5896831136236704
|
||||
B5_mofe_mlp,3407,all_modalities_10,AV,0.39947802197802196,0.3873626373626374,0.32667745632365675,0.8781698942184448,0.28384183315332934
|
||||
B5_mofe_mlp,3407,all_modalities_10,TAV,0.39947802197802196,0.5796703296703297,0.5603794485883429,0.6692947745323181,0.5686062320633599
|
||||
B5_mofe_mlp,3407,text_20,T,0.4073076923076923,0.6016483516483516,0.5744089403315806,0.6390801072120667,0.6021358626478962
|
||||
B5_mofe_mlp,3407,text_20,A,0.4704945054945055,0.4642857142857143,0.2494552539431357,0.8059768080711365,0.07746180938998821
|
||||
B5_mofe_mlp,3407,text_20,V,0.44483516483516483,0.45467032967032966,0.38380648966660313,0.793641984462738,0.24830688010478227
|
||||
B5_mofe_mlp,3407,text_20,TA,0.37112637362637363,0.5741758241758241,0.5418661031211773,0.6627365350723267,0.5604770780530056
|
||||
B5_mofe_mlp,3407,text_20,TV,0.3507142857142857,0.603021978021978,0.5357923985725986,0.6560192704200745,0.5732426799450642
|
||||
B5_mofe_mlp,3407,text_20,AV,0.44483516483516483,0.3791208791208791,0.3126586105031628,0.8910257816314697,0.25653375730622274
|
||||
B5_mofe_mlp,3407,text_20,TAV,0.3507142857142857,0.5934065934065934,0.5604543054498898,0.6754387021064758,0.5450045102927684
|
||||
B5_mofe_mlp,3407,audio_20,T,0.5117582417582418,0.6002747252747253,0.5893745342941709,0.6272591948509216,0.6221016794037438
|
||||
B5_mofe_mlp,3407,audio_20,A,0.37486263736263736,0.4945054945054945,0.3373484461000103,0.7447602152824402,0.3567553342617643
|
||||
B5_mofe_mlp,3407,audio_20,V,0.44483516483516483,0.46016483516483514,0.3944283930013793,0.7885401844978333,0.2723842014763785
|
||||
B5_mofe_mlp,3407,audio_20,TA,0.37486263736263736,0.5975274725274725,0.5831680958487365,0.6350199580192566,0.5940990561424356
|
||||
B5_mofe_mlp,3407,audio_20,TV,0.44483516483516483,0.6167582417582418,0.5667282248122798,0.6437039971351624,0.5927168852036161
|
||||
B5_mofe_mlp,3407,audio_20,AV,0.354010989010989,0.4697802197802198,0.42693867646678624,0.8040833473205566,0.41986361746775985
|
||||
B5_mofe_mlp,3407,audio_20,TAV,0.354010989010989,0.6002747252747253,0.5813735202449936,0.6587744355201721,0.5783158306220523
|
||||
B5_mofe_mlp,3407,vision_20,T,0.5117582417582418,0.6002747252747253,0.5892252758196194,0.6273123025894165,0.6225084305561861
|
||||
B5_mofe_mlp,3407,vision_20,A,0.4704945054945055,0.4684065934065934,0.25920850508591314,0.8053038716316223,0.0857924968918223
|
||||
B5_mofe_mlp,3407,vision_20,V,0.3525,0.5288461538461539,0.4720058888479941,0.7252842783927917,0.41317316472128224
|
||||
B5_mofe_mlp,3407,vision_20,TA,0.4704945054945055,0.5824175824175825,0.5670673740607254,0.6420119404792786,0.5840681638144474
|
||||
B5_mofe_mlp,3407,vision_20,TV,0.3525,0.625,0.5781351467902999,0.6339039206504822,0.5999731536004191
|
||||
B5_mofe_mlp,3407,vision_20,AV,0.3525,0.47802197802197804,0.4364142415752362,0.7915684580802917,0.4020387452763518
|
||||
B5_mofe_mlp,3407,vision_20,TAV,0.3525,0.6181318681318682,0.5982469512967439,0.656253457069397,0.5726154591849658
|
||||
B5_mofe_mlp,3407,audio_vision_20,T,0.5117582417582418,0.5989010989010989,0.5883115478052187,0.627071738243103,0.6227612439489552
|
||||
B5_mofe_mlp,3407,audio_vision_20,A,0.36782967032967034,0.5123626373626373,0.3814657210401891,0.7518494725227356,0.3353158204477575
|
||||
B5_mofe_mlp,3407,audio_vision_20,V,0.3472802197802198,0.5247252747252747,0.4843248302906597,0.7358435392379761,0.4214120030770159
|
||||
B5_mofe_mlp,3407,audio_vision_20,TA,0.36782967032967034,0.6002747252747253,0.5892792851694453,0.628782331943512,0.6006774631204904
|
||||
B5_mofe_mlp,3407,audio_vision_20,TV,0.3472802197802198,0.6332417582417582,0.5964419732456347,0.6303027868270874,0.6076400985344274
|
||||
B5_mofe_mlp,3407,audio_vision_20,AV,0.3472802197802198,0.46565934065934067,0.4355944055944056,0.8029803037643433,0.41656408552542945
|
||||
B5_mofe_mlp,3407,audio_vision_20,TAV,0.3472802197802198,0.6002747252747253,0.5862363095320736,0.6544462442398071,0.585378630597988
|
||||
B5_mofe_mlp,3407,all_modalities_20,T,0.40958791208791206,0.6002747252747253,0.5899048320687862,0.6346542239189148,0.61001396406442
|
||||
B5_mofe_mlp,3407,all_modalities_20,A,0.37326923076923074,0.4739010989010989,0.27165625210557365,0.8040055632591248,0.10424718487552988
|
||||
B5_mofe_mlp,3407,all_modalities_20,V,0.35244505494505496,0.4642857142857143,0.40252151018656984,0.7802431583404541,0.29135083510415233
|
||||
B5_mofe_mlp,3407,all_modalities_20,TA,0.37326923076923074,0.5686813186813187,0.5572575422788313,0.6487621665000916,0.5725190946033569
|
||||
B5_mofe_mlp,3407,all_modalities_20,TV,0.35244505494505496,0.6126373626373627,0.5629491230638092,0.649815022945404,0.5810131620167055
|
||||
B5_mofe_mlp,3407,all_modalities_20,AV,0.35244505494505496,0.3956043956043956,0.3405710346065853,0.8701844215393066,0.3057071868398566
|
||||
B5_mofe_mlp,3407,all_modalities_20,TAV,0.35244505494505496,0.5837912087912088,0.5631923344724951,0.6739726066589355,0.559728652392748
|
||||
B5_mofe_mlp,3407,text_30,T,0.36063186813186815,0.6112637362637363,0.5806932321558671,0.6485379934310913,0.5795620041997364
|
||||
B5_mofe_mlp,3407,text_30,A,0.4704945054945055,0.46703296703296704,0.2536900771342752,0.8093824982643127,0.062449346059579636
|
||||
B5_mofe_mlp,3407,text_30,V,0.44483516483516483,0.4409340659340659,0.3710188660549014,0.7965743541717529,0.24688085844704077
|
||||
B5_mofe_mlp,3407,text_30,TA,0.32774725274725275,0.592032967032967,0.5537539943729123,0.6646007299423218,0.539540874633729
|
||||
B5_mofe_mlp,3407,text_30,TV,0.3087362637362637,0.6016483516483516,0.5385391277047284,0.661797046661377,0.553382704054472
|
||||
B5_mofe_mlp,3407,text_30,AV,0.44483516483516483,0.37225274725274726,0.3029182824443429,0.8928881883621216,0.2563737225632936
|
||||
B5_mofe_mlp,3407,text_30,TAV,0.3087362637362637,0.5865384615384616,0.5490273643806375,0.6738437414169312,0.5345429616136375
|
||||
B5_mofe_mlp,3407,audio_30,T,0.5117582417582418,0.6002747252747253,0.5893745342941709,0.6269524693489075,0.6225361454710463
|
||||
B5_mofe_mlp,3407,audio_30,A,0.3245879120879121,0.532967032967033,0.41756519321424274,0.7341850399971008,0.4112199578484464
|
||||
B5_mofe_mlp,3407,audio_30,V,0.44483516483516483,0.45054945054945056,0.3832106337593439,0.7885648012161255,0.2735580453202714
|
||||
B5_mofe_mlp,3407,audio_30,TA,0.3245879120879121,0.6085164835164835,0.5930238521146932,0.6325163841247559,0.5979866887810961
|
||||
B5_mofe_mlp,3407,audio_30,TV,0.44483516483516483,0.6112637362637363,0.5583419641348294,0.6421341896057129,0.5937514392972938
|
||||
B5_mofe_mlp,3407,audio_30,AV,0.3048351648351648,0.5,0.4623444097193838,0.7733940482139587,0.4553589708631863
|
||||
B5_mofe_mlp,3407,audio_30,TAV,0.3048351648351648,0.614010989010989,0.5938581135634877,0.6490943431854248,0.5943926321157222
|
||||
B5_mofe_mlp,3407,vision_30,T,0.5117582417582418,0.5989010989010989,0.5879942456720697,0.6273198127746582,0.6227160564904063
|
||||
B5_mofe_mlp,3407,vision_30,A,0.4704945054945055,0.4697802197802198,0.26181694968773733,0.8051190972328186,0.08667352225368381
|
||||
B5_mofe_mlp,3407,vision_30,V,0.3087087912087912,0.5233516483516484,0.461764143838227,0.7223021984100342,0.42618344773653233
|
||||
B5_mofe_mlp,3407,vision_30,TA,0.4704945054945055,0.5824175824175825,0.5672280279314932,0.6419575810432434,0.5838877628981125
|
||||
B5_mofe_mlp,3407,vision_30,TV,0.3087087912087912,0.6112637362637363,0.5662069378393744,0.641978919506073,0.5924386628826628
|
||||
B5_mofe_mlp,3407,vision_30,AV,0.3087087912087912,0.49862637362637363,0.445456810889948,0.7776786088943481,0.4216009067968943
|
||||
B5_mofe_mlp,3407,vision_30,TAV,0.3087087912087912,0.6071428571428571,0.5854633810737848,0.6539670825004578,0.575092050206525
|
||||
B5_mofe_mlp,3407,audio_vision_30,T,0.5117582417582418,0.6002747252747253,0.5893745342941709,0.627665102481842,0.6221384257612228
|
||||
B5_mofe_mlp,3407,audio_vision_30,A,0.3249725274725275,0.5425824175824175,0.43415828421831115,0.7195268273353577,0.42527940515455587
|
||||
B5_mofe_mlp,3407,audio_vision_30,V,0.3061813186813187,0.5521978021978022,0.5104487621775328,0.7024397253990173,0.48245172490908617
|
||||
B5_mofe_mlp,3407,audio_vision_30,TA,0.3249725274725275,0.6085164835164835,0.5960454962258536,0.6273004412651062,0.6054657619733786
|
||||
B5_mofe_mlp,3407,audio_vision_30,TV,0.3061813186813187,0.6195054945054945,0.5821910607231708,0.6338788866996765,0.6053650582969483
|
||||
B5_mofe_mlp,3407,audio_vision_30,AV,0.3061813186813187,0.510989010989011,0.4810449552418117,0.7675954103469849,0.4618091165069954
|
||||
B5_mofe_mlp,3407,audio_vision_30,TAV,0.3061813186813187,0.6085164835164835,0.5928020993486814,0.6524761319160461,0.5899471775250983
|
||||
B5_mofe_mlp,3407,all_modalities_30,T,0.3557967032967033,0.6057692307692307,0.5973699542180001,0.636671781539917,0.6031831013481838
|
||||
B5_mofe_mlp,3407,all_modalities_30,A,0.32255494505494503,0.47802197802197804,0.2858992684718562,0.7997275590896606,0.12003229290681895
|
||||
B5_mofe_mlp,3407,all_modalities_30,V,0.3045879120879121,0.49175824175824173,0.4332501168084348,0.7785677909851074,0.28114128593778215
|
||||
B5_mofe_mlp,3407,all_modalities_30,TA,0.32255494505494503,0.5755494505494505,0.5618376925923627,0.6488230228424072,0.5646887050197861
|
||||
B5_mofe_mlp,3407,all_modalities_30,TV,0.3045879120879121,0.6153846153846154,0.569951909037207,0.6524091362953186,0.5765149523517863
|
||||
B5_mofe_mlp,3407,all_modalities_30,AV,0.3045879120879121,0.41208791208791207,0.3552498095654271,0.860482931137085,0.28184827867802903
|
||||
B5_mofe_mlp,3407,all_modalities_30,TAV,0.3045879120879121,0.5741758241758241,0.5572916475321001,0.676213800907135,0.5462438459585837
|
||||
B5_mofe_mlp,2026,clean,T,0.5117582417582418,0.6126373626373627,0.596773495897157,0.6489740014076233,0.6011464226614753
|
||||
B5_mofe_mlp,2026,clean,A,0.4704945054945055,0.4725274725274725,0.2753954425047768,0.8250412344932556,0.2298903607017162
|
||||
B5_mofe_mlp,2026,clean,V,0.44483516483516483,0.5151098901098901,0.41609693688045696,0.741955578327179,0.33524135089906154
|
||||
B5_mofe_mlp,2026,clean,TA,0.4704945054945055,0.592032967032967,0.5532162058371736,0.6664568185806274,0.559760822402557
|
||||
B5_mofe_mlp,2026,clean,TV,0.44483516483516483,0.592032967032967,0.5774206516713903,0.7040248513221741,0.566471089961779
|
||||
B5_mofe_mlp,2026,clean,AV,0.44483516483516483,0.3626373626373626,0.34907979624206836,0.8443424105644226,0.23675835533866071
|
||||
B5_mofe_mlp,2026,clean,TAV,0.44483516483516483,0.5370879120879121,0.4651554172647243,0.800514817237854,0.5127573095239696
|
||||
B5_mofe_mlp,2026,text_10,T,0.4616758241758242,0.6126373626373627,0.5930164703753459,0.6494342088699341,0.5946752236527758
|
||||
B5_mofe_mlp,2026,text_10,A,0.4704945054945055,0.4725274725274725,0.27541290783115796,0.8262399435043335,0.22445377406080036
|
||||
B5_mofe_mlp,2026,text_10,V,0.44483516483516483,0.5123626373626373,0.41266149205541813,0.7444266080856323,0.3297960027909343
|
||||
B5_mofe_mlp,2026,text_10,TA,0.42304945054945053,0.5837912087912088,0.5397729831672579,0.6658428907394409,0.5527226500907891
|
||||
B5_mofe_mlp,2026,text_10,TV,0.4,0.592032967032967,0.571111408272237,0.6985096335411072,0.5560292322354257
|
||||
B5_mofe_mlp,2026,text_10,AV,0.44483516483516483,0.3585164835164835,0.34496753089852183,0.8458796739578247,0.23343562747276608
|
||||
B5_mofe_mlp,2026,text_10,TAV,0.4,0.5384615384615384,0.4615912536399786,0.7843563556671143,0.4964631006483741
|
||||
B5_mofe_mlp,2026,audio_10,T,0.5117582417582418,0.6112637362637363,0.594775223911222,0.6496217250823975,0.6011032755471458
|
||||
B5_mofe_mlp,2026,audio_10,A,0.4226373626373626,0.489010989010989,0.30986648206415496,0.795183539390564,0.32899907907949955
|
||||
B5_mofe_mlp,2026,audio_10,V,0.44483516483516483,0.5164835164835165,0.41734454924869885,0.7415561079978943,0.3356207601336875
|
||||
B5_mofe_mlp,2026,audio_10,TA,0.4226373626373626,0.5906593406593407,0.5523948427986319,0.6616610884666443,0.565696879589075
|
||||
B5_mofe_mlp,2026,audio_10,TV,0.44483516483516483,0.5906593406593407,0.5756793112725316,0.7050058841705322,0.5670178444167456
|
||||
B5_mofe_mlp,2026,audio_10,AV,0.3998076923076923,0.40796703296703296,0.4021505731323723,0.8058488368988037,0.339145168854004
|
||||
B5_mofe_mlp,2026,audio_10,TAV,0.3998076923076923,0.5604395604395604,0.5020907193394417,0.7697135210037231,0.5332348529741537
|
||||
B5_mofe_mlp,2026,vision_10,T,0.5117582417582418,0.6112637362637363,0.5949280494683542,0.6487315893173218,0.6010584792844983
|
||||
B5_mofe_mlp,2026,vision_10,A,0.4704945054945055,0.4725274725274725,0.2753954425047768,0.8233988285064697,0.2309789028597694
|
||||
B5_mofe_mlp,2026,vision_10,V,0.39843406593406594,0.5398351648351648,0.43853463696042566,0.714551568031311,0.4295200457733584
|
||||
B5_mofe_mlp,2026,vision_10,TA,0.4704945054945055,0.592032967032967,0.5532162058371736,0.6668616533279419,0.5594488174710718
|
||||
B5_mofe_mlp,2026,vision_10,TV,0.39843406593406594,0.6016483516483516,0.5819547002883038,0.6787747144699097,0.5779704513615178
|
||||
B5_mofe_mlp,2026,vision_10,AV,0.39843406593406594,0.4258241758241758,0.42253912572720753,0.7936479449272156,0.36127841752536083
|
||||
B5_mofe_mlp,2026,vision_10,TAV,0.39843406593406594,0.5714285714285714,0.5087225335512859,0.760180652141571,0.5350946573582769
|
||||
B5_mofe_mlp,2026,audio_vision_10,T,0.5117582417582418,0.614010989010989,0.5982455160173181,0.6492474675178528,0.6011554930046857
|
||||
B5_mofe_mlp,2026,audio_vision_10,A,0.4210714285714286,0.4876373626373626,0.3042744149605441,0.7851645350456238,0.3562020191286223
|
||||
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B5_mofe_mlp,2026,audio_vision_10,TA,0.4210714285714286,0.5934065934065934,0.559867581706166,0.6601359844207764,0.5680404697940684
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B5_mofe_mlp,2026,audio_vision_10,TV,0.39807692307692305,0.6002747252747253,0.5842152460266312,0.6859722137451172,0.5754538071328372
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B5_mofe_mlp,2026,text_20,TA,0.37524725274725274,0.603021978021978,0.5486119524164519,0.6673293113708496,0.539250704149763
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B5_mofe_mlp,2026,text_20,TV,0.3546153846153846,0.6112637362637363,0.5843667494564081,0.6891446113586426,0.5445040624635075
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B5_mofe_mlp,2026,text_20,AV,0.44483516483516483,0.3585164835164835,0.3446302940469433,0.8487928509712219,0.21264829535541369
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B5_mofe_mlp,2026,text_20,TAV,0.3546153846153846,0.5425824175824175,0.46587133463364855,0.7634089589118958,0.4821419242332205
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B5_mofe_mlp,2026,audio_20,T,0.5117582417582418,0.614010989010989,0.5983472125624337,0.6503203511238098,0.6009217826600645
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B5_mofe_mlp,2026,audio_20,A,0.3796978021978022,0.5164835164835165,0.3655881236095169,0.7692446112632751,0.3949787935175758
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B5_mofe_mlp,2026,audio_20,V,0.44483516483516483,0.5151098901098901,0.41620583054274807,0.7414965629577637,0.3344494005058201
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B5_mofe_mlp,2026,audio_20,TA,0.3796978021978022,0.5989010989010989,0.5638265304840163,0.6491043567657471,0.5770018901388131
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B5_mofe_mlp,2026,audio_20,TV,0.44483516483516483,0.592032967032967,0.5774181294613681,0.7061969041824341,0.5658046441453625
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B5_mofe_mlp,2026,audio_20,AV,0.3596153846153846,0.4793956043956044,0.4729905027892644,0.7711812257766724,0.39212697776164607
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B5_mofe_mlp,2026,audio_20,TAV,0.3596153846153846,0.5645604395604396,0.509050719882809,0.7490760684013367,0.534134549592931
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B5_mofe_mlp,2026,vision_20,T,0.5117582417582418,0.6126373626373627,0.5965577523042379,0.6482208371162415,0.6014238929804235
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B5_mofe_mlp,2026,vision_20,A,0.4704945054945055,0.4725274725274725,0.2753954425047768,0.8218814730644226,0.2303172585691777
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B5_mofe_mlp,2026,vision_20,V,0.3572802197802198,0.5480769230769231,0.45491017561200736,0.7200025916099548,0.4188711113417921
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B5_mofe_mlp,2026,vision_20,TA,0.4704945054945055,0.592032967032967,0.5532162058371736,0.6667655110359192,0.5596751462352669
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B5_mofe_mlp,2026,vision_20,TV,0.3572802197802198,0.6085164835164835,0.5858009850150654,0.6767599582672119,0.5666763660374662
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B5_mofe_mlp,2026,vision_20,AV,0.3572802197802198,0.45604395604395603,0.45257735286592293,0.7822015881538391,0.3511756724909663
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B5_mofe_mlp,2026,vision_20,TAV,0.3572802197802198,0.5673076923076923,0.5113134010717539,0.7461904883384705,0.5258941930408034
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B5_mofe_mlp,2026,audio_vision_20,T,0.5117582417582418,0.614010989010989,0.5983472125624337,0.6493008136749268,0.6012901521222299
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B5_mofe_mlp,2026,audio_vision_20,V,0.3531593406593407,0.5796703296703297,0.5048183867639185,0.6984941363334656,0.4714365355794056
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B5_mofe_mlp,2026,audio_vision_20,TA,0.372967032967033,0.5892857142857143,0.5573263153954385,0.6522572040557861,0.5764869480931716
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B5_mofe_mlp,2026,audio_vision_20,TV,0.3531593406593407,0.6057692307692307,0.5884441789459711,0.6706872582435608,0.5818979616306791
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B5_mofe_mlp,2026,audio_vision_20,AV,0.3531593406593407,0.4684065934065934,0.465468176106474,0.7679478526115417,0.41865980844292155
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B5_mofe_mlp,2026,audio_vision_20,TAV,0.3531593406593407,0.5728021978021978,0.5181235721920635,0.7481652498245239,0.5424180387206542
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B5_mofe_mlp,2026,all_modalities_20,T,0.40585164835164833,0.6057692307692307,0.5895572046059541,0.6424160003662109,0.5987483157591782
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B5_mofe_mlp,2026,text_30,V,0.44483516483516483,0.5041208791208791,0.40060701323330045,0.7515881657600403,0.30841065019819836
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B5_mofe_mlp,2026,text_30,TAV,0.3089010989010989,0.5343406593406593,0.45069366576352604,0.7611382603645325,0.4366871235743856
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B5_mofe_mlp,2026,audio_30,V,0.44483516483516483,0.5151098901098901,0.4189500868178652,0.7407843470573425,0.33537420437520643
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B5_mofe_mlp,2026,audio_30,AV,0.3078021978021978,0.4876373626373626,0.4781988617789497,0.7588927745819092,0.41241620046706
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B5_mofe_mlp,2026,audio_30,TAV,0.3078021978021978,0.5796703296703297,0.5254621943407217,0.7300676703453064,0.5331740795732829
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B5_mofe_mlp,2026,vision_30,T,0.5117582417582418,0.6112637362637363,0.5951956697149005,0.648055374622345,0.6013618141882758
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B5_mofe_mlp,2026,vision_30,AV,0.3076098901098901,0.4835164835164835,0.4758194996023056,0.7574149370193481,0.39536651435197256
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B5_mofe_mlp,2026,vision_30,TAV,0.3076098901098901,0.5851648351648352,0.5229046773276295,0.7180534601211548,0.5426270178162265
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B5_mofe_mlp,2026,audio_vision_30,T,0.5117582417582418,0.6126373626373627,0.5966200968456806,0.6497841477394104,0.6010003821616935
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B5_mofe_mlp,2026,audio_vision_30,TA,0.31903846153846155,0.5906593406593407,0.5620402015554825,0.6461182832717896,0.5751739998185288
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B5_mofe_mlp,2026,audio_vision_30,TV,0.30107142857142855,0.6167582417582418,0.6003175316510284,0.6656390428543091,0.5833224225343602
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B5_mofe_mlp,2026,audio_vision_30,AV,0.30107142857142855,0.5,0.49814761477760233,0.7473122477531433,0.43986219237598306
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B5_mofe_mlp,2026,audio_vision_30,TAV,0.30107142857142855,0.5673076923076923,0.5181807136427148,0.7298097610473633,0.5492606185227297
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|
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|
||||
B5_mofe_mlp,42,all_modalities_20,0.2,728,0.6401098901098901,0.6082957983542778,0.6285881400108337,0.6113174240287709
|
||||
B5_mofe_mlp,42,text_30,0.3,728,0.614010989010989,0.5665382052109811,0.6587778925895691,0.57122460274951
|
||||
B5_mofe_mlp,42,audio_30,0.3,728,0.6414835164835165,0.6099992622632019,0.6212661266326904,0.6127160793050621
|
||||
B5_mofe_mlp,42,vision_30,0.3,728,0.6442307692307693,0.6100360167586674,0.6305183172225952,0.6127016894323144
|
||||
B5_mofe_mlp,42,audio_vision_30,0.3,728,0.6538461538461539,0.6220936984876739,0.6240691542625427,0.6123047623188541
|
||||
B5_mofe_mlp,42,all_modalities_30,0.3,728,0.6442307692307693,0.6106062664769548,0.6119968295097351,0.6240023303690699
|
||||
B0_early_concat,3407,clean,0.0,728,0.6332417582417582,0.5937554950072336,0.6333680152893066,0.6138300851146614
|
||||
B0_early_concat,3407,text_10,0.1,728,0.6277472527472527,0.5848809977670061,0.6363487243652344,0.6056385881925804
|
||||
B0_early_concat,3407,audio_10,0.1,728,0.635989010989011,0.5968950441819239,0.6318458914756775,0.6158991549580464
|
||||
B0_early_concat,3407,vision_10,0.1,728,0.6332417582417582,0.5933513166880985,0.6328762769699097,0.614296568855868
|
||||
B0_early_concat,3407,audio_vision_10,0.1,728,0.635989010989011,0.5972272747847399,0.6317789554595947,0.613152110576325
|
||||
B0_early_concat,3407,all_modalities_10,0.1,728,0.6208791208791209,0.5757563714642701,0.6323474645614624,0.617483663695453
|
||||
B0_early_concat,3407,text_20,0.2,728,0.6043956043956044,0.5490811521155289,0.6509508490562439,0.5895223268279027
|
||||
B0_early_concat,3407,audio_20,0.2,728,0.635989010989011,0.5977119556159886,0.6304426789283752,0.6183830231575858
|
||||
B0_early_concat,3407,vision_20,0.2,728,0.6401098901098901,0.6034867151810619,0.628890335559845,0.6187934526699497
|
||||
B0_early_concat,3407,audio_vision_20,0.2,728,0.6346153846153846,0.600406263153788,0.633434534072876,0.6123211847883981
|
||||
B0_early_concat,3407,all_modalities_20,0.2,728,0.6153846153846154,0.5731546231546232,0.6435555815696716,0.6001160788677808
|
||||
B0_early_concat,3407,text_30,0.3,728,0.6071428571428571,0.5572172310238351,0.6613345146179199,0.5663984672630126
|
||||
B0_early_concat,3407,audio_30,0.3,728,0.6401098901098901,0.602821099359954,0.6328924298286438,0.6157652906372406
|
||||
B0_early_concat,3407,vision_30,0.3,728,0.6277472527472527,0.5882423141524775,0.6326207518577576,0.6153119497189492
|
||||
B0_early_concat,3407,audio_vision_30,0.3,728,0.6428571428571429,0.6062757576614914,0.6341086030006409,0.6170348487651544
|
||||
B0_early_concat,3407,all_modalities_30,0.3,728,0.6277472527472527,0.5839727159969967,0.6468587517738342,0.5966126256796758
|
||||
B5_mofe_mlp,3407,clean,0.0,728,0.635989010989011,0.604973907499834,0.6324349641799927,0.6151046893704437
|
||||
B5_mofe_mlp,3407,text_10,0.1,728,0.6318681318681318,0.5933228635123383,0.633339524269104,0.6112816469725518
|
||||
B5_mofe_mlp,3407,audio_10,0.1,728,0.635989010989011,0.6042690508274062,0.6318331360816956,0.6144226554849131
|
||||
B5_mofe_mlp,3407,vision_10,0.1,728,0.6387362637362637,0.6078729015399154,0.6297808885574341,0.6157341874415431
|
||||
B5_mofe_mlp,3407,audio_vision_10,0.1,728,0.625,0.5961079542334627,0.630139172077179,0.6148226006976545
|
||||
B5_mofe_mlp,3407,all_modalities_10,0.1,728,0.6195054945054945,0.5890880499595165,0.6359822750091553,0.6113081804637202
|
||||
B5_mofe_mlp,3407,text_20,0.2,728,0.6195054945054945,0.5755820027236789,0.6454524993896484,0.5935605745999009
|
||||
B5_mofe_mlp,3407,audio_20,0.2,728,0.6332417582417582,0.6046231856798019,0.6310902833938599,0.6172434930698147
|
||||
B5_mofe_mlp,3407,vision_20,0.2,728,0.635989010989011,0.6063745521197687,0.6304876208305359,0.6140966581910975
|
||||
B5_mofe_mlp,3407,audio_vision_20,0.2,728,0.635989010989011,0.609224910808655,0.6240154504776001,0.6185046337968831
|
||||
B5_mofe_mlp,3407,all_modalities_20,0.2,728,0.6332417582417582,0.6079307048305954,0.634419858455658,0.6044717652490789
|
||||
B5_mofe_mlp,3407,text_30,0.3,728,0.6181318681318682,0.5733540937906745,0.656674325466156,0.5668925651895068
|
||||
B5_mofe_mlp,3407,audio_30,0.3,728,0.6332417582417582,0.604260667390971,0.6289573907852173,0.617381543407622
|
||||
B5_mofe_mlp,3407,vision_30,0.3,728,0.6332417582417582,0.6016029959347541,0.6318032145500183,0.6125144777620533
|
||||
B5_mofe_mlp,3407,audio_vision_30,0.3,728,0.6318681318681318,0.6067614810631058,0.6228161454200745,0.621408382664964
|
||||
B5_mofe_mlp,3407,all_modalities_30,0.3,728,0.6222527472527473,0.5949881199577279,0.6458109021186829,0.5977781285960149
|
||||
B0_early_concat,2026,clean,0.0,728,0.6112637362637363,0.5592125291749822,0.6401797533035278,0.6097643309752457
|
||||
B0_early_concat,2026,text_10,0.1,728,0.6098901098901099,0.5538253146595995,0.6407675743103027,0.60352101329599
|
||||
B0_early_concat,2026,audio_10,0.1,728,0.614010989010989,0.5630983962746592,0.6385665535926819,0.6110860034615799
|
||||
B0_early_concat,2026,vision_10,0.1,728,0.6181318681318682,0.5661140652625988,0.6405577659606934,0.6110400519655834
|
||||
B0_early_concat,2026,audio_vision_10,0.1,728,0.6098901098901099,0.5587567567850849,0.6381099224090576,0.6107705746373118
|
||||
B0_early_concat,2026,all_modalities_10,0.1,728,0.614010989010989,0.5581636747439855,0.6429373621940613,0.6088956503302468
|
||||
B0_early_concat,2026,text_20,0.2,728,0.6043956043956044,0.5429151983962918,0.6489536762237549,0.5886848272694757
|
||||
B0_early_concat,2026,audio_20,0.2,728,0.6112637362637363,0.5603026186889267,0.636631965637207,0.6105368420749809
|
||||
B0_early_concat,2026,vision_20,0.2,728,0.614010989010989,0.5607756511971072,0.6439995765686035,0.6079712010559852
|
||||
B0_early_concat,2026,audio_vision_20,0.2,728,0.6181318681318682,0.5696462960623787,0.6381081342697144,0.6114528658433437
|
||||
B0_early_concat,2026,all_modalities_20,0.2,728,0.6085164835164835,0.5508998902588577,0.6492584347724915,0.6012091639944216
|
||||
B0_early_concat,2026,text_30,0.3,728,0.5851648351648352,0.5160231153138954,0.6731752753257751,0.5521914713018387
|
||||
B0_early_concat,2026,audio_30,0.3,728,0.6181318681318682,0.5670636517410711,0.636723518371582,0.6097718223127288
|
||||
B0_early_concat,2026,vision_30,0.3,728,0.6085164835164835,0.5560149900702367,0.6435868144035339,0.609850184236316
|
||||
B0_early_concat,2026,audio_vision_30,0.3,728,0.6098901098901099,0.5653848813301509,0.637891948223114,0.6075333578422618
|
||||
B0_early_concat,2026,all_modalities_30,0.3,728,0.6043956043956044,0.5496991187074715,0.6696622371673584,0.5843647118157551
|
||||
B5_mofe_mlp,2026,clean,0.0,728,0.6318681318681318,0.596526187825028,0.6597292423248291,0.6032696127085834
|
||||
B5_mofe_mlp,2026,text_10,0.1,728,0.6332417582417582,0.5928689292978023,0.6584991812705994,0.5961609550472456
|
||||
B5_mofe_mlp,2026,audio_10,0.1,728,0.6332417582417582,0.5971419540706502,0.6580070853233337,0.6047899048858725
|
||||
B5_mofe_mlp,2026,vision_10,0.1,728,0.6277472527472527,0.5919759280299669,0.6596941947937012,0.6023122703551795
|
||||
B5_mofe_mlp,2026,audio_vision_10,0.1,728,0.6291208791208791,0.5949724164706738,0.6590589880943298,0.60347148906883
|
||||
B5_mofe_mlp,2026,all_modalities_10,0.1,728,0.6387362637362637,0.6013762119617033,0.6582632660865784,0.599810574437488
|
||||
B5_mofe_mlp,2026,text_20,0.2,728,0.6277472527472527,0.579286730359655,0.667361319065094,0.582974915319036
|
||||
B5_mofe_mlp,2026,audio_20,0.2,728,0.6304945054945055,0.5954536143668596,0.6568871736526489,0.6037190808626715
|
||||
B5_mofe_mlp,2026,vision_20,0.2,728,0.6277472527472527,0.5900160130008749,0.6632898449897766,0.6042443916006178
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.2,728,0.625,0.5917418600128784,0.6548266410827637,0.6054018359666251
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.2,728,0.6387362637362637,0.6023597229130889,0.6525924801826477,0.6015383340552747
|
||||
B5_mofe_mlp,2026,text_30,0.3,728,0.6236263736263736,0.5695777746219127,0.6862288117408752,0.5485307064435356
|
||||
B5_mofe_mlp,2026,audio_30,0.3,728,0.6277472527472527,0.5928207016211315,0.656401515007019,0.605701200975301
|
||||
B5_mofe_mlp,2026,vision_30,0.3,728,0.6291208791208791,0.5902326768980343,0.6632499694824219,0.6060668503667017
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.3,728,0.625,0.5962838833608418,0.6554995775222778,0.6044591409783642
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.3,728,0.6167582417582418,0.5778458150682998,0.6775780916213989,0.5767909598557909
|
||||
|
+49
@@ -0,0 +1,49 @@
|
||||
method,seed,condition,utility_text_mean,utility_audio_mean,utility_vision_mean
|
||||
B5_mofe_mlp,42,clean,0.6618766188621521,0.5899914503097534,0.5503968000411987
|
||||
B5_mofe_mlp,42,text_10,0.6631303429603577,0.6045999526977539,0.5672140121459961
|
||||
B5_mofe_mlp,42,audio_10,0.6753877997398376,0.5900472402572632,0.5553804636001587
|
||||
B5_mofe_mlp,42,vision_10,0.6722928285598755,0.5894219875335693,0.5504083633422852
|
||||
B5_mofe_mlp,42,audio_vision_10,0.6965795755386353,0.5897499918937683,0.5503614544868469
|
||||
B5_mofe_mlp,42,all_modalities_10,0.663243293762207,0.5896329879760742,0.5504105091094971
|
||||
B5_mofe_mlp,42,text_20,0.6646575927734375,0.6176748275756836,0.5843319892883301
|
||||
B5_mofe_mlp,42,audio_20,0.6875958442687988,0.5900545716285706,0.5599780678749084
|
||||
B5_mofe_mlp,42,vision_20,0.6815856695175171,0.5894845128059387,0.5504598617553711
|
||||
B5_mofe_mlp,42,audio_vision_20,0.7309128642082214,0.5897306203842163,0.5503560900688171
|
||||
B5_mofe_mlp,42,all_modalities_20,0.6649715900421143,0.589468240737915,0.5503589510917664
|
||||
B5_mofe_mlp,42,text_30,0.6656913161277771,0.6293779611587524,0.5994364023208618
|
||||
B5_mofe_mlp,42,audio_30,0.7017264366149902,0.5900580883026123,0.5654440522193909
|
||||
B5_mofe_mlp,42,vision_30,0.6905444860458374,0.5895596742630005,0.5504684448242188
|
||||
B5_mofe_mlp,42,audio_vision_30,0.7655619382858276,0.5896934866905212,0.5503290891647339
|
||||
B5_mofe_mlp,42,all_modalities_30,0.666799783706665,0.5894308686256409,0.5503942370414734
|
||||
B5_mofe_mlp,3407,clean,0.5965457558631897,0.6089583039283752,0.5700515508651733
|
||||
B5_mofe_mlp,3407,text_10,0.5980162024497986,0.6175488829612732,0.5699793100357056
|
||||
B5_mofe_mlp,3407,audio_10,0.6005110144615173,0.6088259816169739,0.5817712545394897
|
||||
B5_mofe_mlp,3407,vision_10,0.602319598197937,0.6167332530021667,0.5697159767150879
|
||||
B5_mofe_mlp,3407,audio_vision_10,0.6381478309631348,0.6084476709365845,0.5697139501571655
|
||||
B5_mofe_mlp,3407,all_modalities_10,0.598029613494873,0.6078585386276245,0.5693216323852539
|
||||
B5_mofe_mlp,3407,text_20,0.6004789471626282,0.6273719668388367,0.5698307156562805
|
||||
B5_mofe_mlp,3407,audio_20,0.604293942451477,0.6087151169776917,0.5934981107711792
|
||||
B5_mofe_mlp,3407,vision_20,0.6091526746749878,0.6249159574508667,0.569640576839447
|
||||
B5_mofe_mlp,3407,audio_vision_20,0.6846911907196045,0.6084182858467102,0.569659948348999
|
||||
B5_mofe_mlp,3407,all_modalities_20,0.6004623174667358,0.607769250869751,0.5691742300987244
|
||||
B5_mofe_mlp,3407,text_30,0.6017250418663025,0.6352017521858215,0.5698606371879578
|
||||
B5_mofe_mlp,3407,audio_30,0.6071357727050781,0.609175980091095,0.6063627004623413
|
||||
B5_mofe_mlp,3407,vision_30,0.6154943108558655,0.6325424909591675,0.5695337653160095
|
||||
B5_mofe_mlp,3407,audio_vision_30,0.7215061783790588,0.6085333228111267,0.5696398019790649
|
||||
B5_mofe_mlp,3407,all_modalities_30,0.6027611494064331,0.6076351404190063,0.5691232085227966
|
||||
B5_mofe_mlp,2026,clean,0.6298863887786865,0.5585612058639526,0.5456792712211609
|
||||
B5_mofe_mlp,2026,text_10,0.6311661005020142,0.571927547454834,0.5534814596176147
|
||||
B5_mofe_mlp,2026,audio_10,0.6393773555755615,0.5580084919929504,0.5503398776054382
|
||||
B5_mofe_mlp,2026,vision_10,0.6332205533981323,0.5693727731704712,0.5460953712463379
|
||||
B5_mofe_mlp,2026,audio_vision_10,0.6685320734977722,0.558728039264679,0.5464425086975098
|
||||
B5_mofe_mlp,2026,all_modalities_10,0.6309354305267334,0.5586868524551392,0.5456184148788452
|
||||
B5_mofe_mlp,2026,text_20,0.6327240467071533,0.5853152871131897,0.5612947344779968
|
||||
B5_mofe_mlp,2026,audio_20,0.6477784514427185,0.557928740978241,0.5547807216644287
|
||||
B5_mofe_mlp,2026,vision_20,0.6358551979064941,0.5790520906448364,0.5461242198944092
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.7063466906547546,0.5585485696792603,0.5466189980506897
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.6332317590713501,0.5591967105865479,0.5456498265266418
|
||||
B5_mofe_mlp,2026,text_30,0.6339558362960815,0.5997033715248108,0.569423258304596
|
||||
B5_mofe_mlp,2026,audio_30,0.658158004283905,0.5578649640083313,0.5603182315826416
|
||||
B5_mofe_mlp,2026,vision_30,0.638981282711029,0.590747058391571,0.5463551878929138
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.7488567233085632,0.5589607357978821,0.5467853546142578
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.6328451037406921,0.5590822696685791,0.5455838441848755
|
||||
|
BIN
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BIN
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BIN
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+6
@@ -0,0 +1,6 @@
|
||||
comparison,candidate,reference,metric,delta_candidate_minus_reference,bootstrap_ci_2p5,bootstrap_ci_97p5,bootstrap_probability_delta_gt_0,bootstrap_replicates,resampling_unit,paired,seed
|
||||
MoFE-7 MLP vs EarlyConcat,B5_mofe_mlp,B0_early_concat,corrupt_macro_f1,0.024555007972419718,0.01160479835525017,0.038111700197624034,0.999,1000,source video id,True,20260924
|
||||
MoFE-7 MLP vs EarlyConcat,B5_mofe_mlp,B0_early_concat,worst_condition_macro_f1,0.023103307323882216,0.007213272437200871,0.04285067710167781,0.996,1000,source video id,True,20260924
|
||||
MoFE-7 MLP vs EarlyConcat,B5_mofe_mlp,B0_early_concat,text_30_macro_f1,0.023103307323882216,0.004027805218645245,0.04212429356920461,0.992,1000,source video id,True,20260924
|
||||
MoFE-7 MLP vs EarlyConcat,B5_mofe_mlp,B0_early_concat,corrupt_mae,0.00036756197611487185,-0.008981325373224738,0.009240262436166205,0.524,1000,source video id,True,20260924
|
||||
MoFE-7 MLP vs EarlyConcat,B5_mofe_mlp,B0_early_concat,corrupt_pearson,-0.0019135250956427985,-0.01366917866941531,0.010852838898108074,0.397,1000,source video id,True,20260924
|
||||
|
@@ -0,0 +1,3 @@
|
||||
method,trainable_parameters,ratio_to_earlyconcat,within_2x_earlyconcat
|
||||
B0_early_concat,253124,1.0,True
|
||||
B5_mofe_mlp,306523,1.2109598457672919,True
|
||||
|
+49
@@ -0,0 +1,49 @@
|
||||
method,seed,condition,active_position_fraction,fallback_position_fraction,normalized_router_entropy,fraction_active_positions_max_weight_over_0p8,alpha_T_mean,alpha_A_mean,alpha_V_mean,alpha_TA_mean,alpha_TV_mean,alpha_AV_mean,alpha_TAV_mean
|
||||
B5_mofe_mlp,42,clean,0.5117582417582418,0.48824175824175825,0.8870560454827882,0.08063130770882543,0.2515257000923157,0.11152571439743042,0.07744884490966797,0.15852881968021393,0.12860679626464844,0.14914916455745697,0.1232161670923233
|
||||
B5_mofe_mlp,42,text_10,0.5092032967032967,0.4907967032967033,0.8506916726514709,0.08211491772322632,0.2304162234067917,0.13068588078022003,0.09430146962404251,0.14338572323322296,0.11664345115423203,0.17277489602565765,0.1117931678891182
|
||||
B5_mofe_mlp,42,audio_10,0.5117582417582418,0.48824175824175825,0.8449963602081583,0.08616061842387804,0.2751412093639374,0.10004748404026031,0.09071236103773117,0.1420598030090332,0.14774158596992493,0.13385255634784698,0.11044659465551376
|
||||
B5_mofe_mlp,42,vision_10,0.5117582417582418,0.48824175824175825,0.8472941162919574,0.08063130770882543,0.2735346555709839,0.1252371221780777,0.06957398355007172,0.1735313981771469,0.11499655246734619,0.13289612531661987,0.11023180931806564
|
||||
B5_mofe_mlp,42,audio_vision_10,0.5117582417582418,0.48824175824175825,0.7958907203885603,0.175434829289242,0.32850298285484314,0.10010535269975662,0.06980907171964645,0.14210578799247742,0.11540128290653229,0.1335059553384781,0.11057072132825851
|
||||
B5_mofe_mlp,42,all_modalities_10,0.4626098901098901,0.5373901098901099,0.8841173799028046,0.08432804798384702,0.2541447579860687,0.11095340549945831,0.07761403918266296,0.15777607262134552,0.1283317655324936,0.14818961918354034,0.12299200892448425
|
||||
B5_mofe_mlp,42,text_20,0.5065384615384615,0.49346153846153845,0.8152469884580759,0.08005206638464042,0.20999735593795776,0.14806155860424042,0.112088643014431,0.12878893315792084,0.10419154912233353,0.19696328043937683,0.09990917891263962
|
||||
B5_mofe_mlp,42,audio_20,0.5117582417582418,0.48824175824175825,0.8069851130815402,0.09013313291818767,0.2962163984775543,0.0896897166967392,0.10295859724283218,0.1273450255393982,0.16525308787822723,0.11975577473640442,0.09878180921077728
|
||||
B5_mofe_mlp,42,vision_20,0.5117582417582418,0.48824175824175825,0.8111495627938943,0.08063130770882543,0.2933293581008911,0.13767293095588684,0.062129102647304535,0.18726874887943268,0.10258819162845612,0.1186119019985199,0.09839928895235062
|
||||
B5_mofe_mlp,42,audio_vision_20,0.5117582417582418,0.48824175824175825,0.7057799858331233,0.2687352372772171,0.40449970960617065,0.08882029354572296,0.06192621961236,0.12605853378772736,0.10232582688331604,0.11834055930376053,0.09802991151809692
|
||||
B5_mofe_mlp,42,all_modalities_20,0.41145604395604396,0.588543956043956,0.8795920971657628,0.08853575482406356,0.25787994265556335,0.11065426468849182,0.07723148167133331,0.157210573554039,0.12760961055755615,0.14714252948760986,0.12227214872837067
|
||||
B5_mofe_mlp,42,text_30,0.5034615384615385,0.49653846153846154,0.7845061109572483,0.07726727054458146,0.19043782353401184,0.164101243019104,0.12816408276557922,0.11582792550325394,0.0932326465845108,0.218837708234787,0.08939971774816513
|
||||
B5_mofe_mlp,42,audio_30,0.5117582417582418,0.48824175824175825,0.7627258720846881,0.09308567747476916,0.32027310132980347,0.0778515487909317,0.11745958030223846,0.11037490516901016,0.18614806234836578,0.10296247154474258,0.08493035286664963
|
||||
B5_mofe_mlp,42,vision_30,0.5117582417582418,0.48824175824175825,0.7764460734868434,0.08063130770882543,0.31232842803001404,0.1496150940656662,0.054964445531368256,0.20050112903118134,0.09068562090396881,0.10487580299377441,0.0870303362607956
|
||||
B5_mofe_mlp,42,audio_vision_30,0.5117582417582418,0.48824175824175825,0.6149186646941948,0.3631092978312218,0.4812489449977875,0.07732704281806946,0.05401867628097534,0.10968495160341263,0.0891624167561531,0.10309218615293503,0.08546625822782516
|
||||
B5_mofe_mlp,42,all_modalities_30,0.3595054945054945,0.6404945054945055,0.8745368649815657,0.09307657038055937,0.26191991567611694,0.11035662144422531,0.07678450644016266,0.1566968709230423,0.12672796845436096,0.14605894684791565,0.12145592272281647
|
||||
B5_mofe_mlp,3407,clean,0.5117582417582418,0.48824175824175825,0.8917789142359226,0.08063130770882543,0.21564963459968567,0.16335873305797577,0.12684088945388794,0.1254868507385254,0.09765232354402542,0.11325515806674957,0.15775780379772186
|
||||
B5_mofe_mlp,3407,text_10,0.509010989010989,0.490989010989011,0.8547805451037497,0.08031088082901554,0.19791889190673828,0.1904035061597824,0.1427920013666153,0.11356116831302643,0.08846957981586456,0.12491724640130997,0.14193856716156006
|
||||
B5_mofe_mlp,3407,audio_10,0.5117582417582418,0.48824175824175825,0.8504781823179828,0.08481855271634099,0.23455235362052917,0.1466052234172821,0.15115498006343842,0.11315018683671951,0.1112954393029213,0.10172916203737259,0.14151319861412048
|
||||
B5_mofe_mlp,3407,vision_10,0.5117582417582418,0.48824175824175825,0.8539108633297741,0.08063130770882543,0.2311594933271408,0.1815430223941803,0.11412636935710907,0.1422722488641739,0.08770900219678879,0.10201089829206467,0.14117981493473053
|
||||
B5_mofe_mlp,3407,audio_vision_10,0.5117582417582418,0.48824175824175825,0.7997980860345286,0.175434829289242,0.29687586426734924,0.14598697423934937,0.11404559761285782,0.11318352073431015,0.08737359195947647,0.10181976109743118,0.14071525633335114
|
||||
B5_mofe_mlp,3407,all_modalities_10,0.4610164835164835,0.5389835164835165,0.8892426095830844,0.08348727727787379,0.2185969352722168,0.16224151849746704,0.12673969566822052,0.12583576142787933,0.09755325317382812,0.11298926174640656,0.1560446321964264
|
||||
B5_mofe_mlp,3407,text_20,0.5066758241758241,0.4933241758241758,0.8130542021789052,0.08176543946212655,0.17931020259857178,0.2202228158712387,0.16002467274665833,0.10018529742956161,0.07809362560510635,0.137038454413414,0.12512563169002533
|
||||
B5_mofe_mlp,3407,audio_20,0.5117582417582418,0.48824175824175825,0.8087283495175436,0.09002576766158471,0.2538429796695709,0.12989234924316406,0.1755901426076889,0.10037955641746521,0.12468340992927551,0.09022346138954163,0.12538877129554749
|
||||
B5_mofe_mlp,3407,vision_20,0.5117582417582418,0.48824175824175825,0.8141886106137566,0.08063130770882543,0.24743759632110596,0.20013628900051117,0.10070110112428665,0.16005626320838928,0.0773327648639679,0.09001021832227707,0.12432596832513809
|
||||
B5_mofe_mlp,3407,audio_vision_20,0.5117582417582418,0.48824175824175825,0.6969105807199653,0.28124328967146234,0.3873015344142914,0.1272396296262741,0.09933283925056458,0.09888661652803421,0.07606082409620285,0.08873630315065384,0.12244285643100739
|
||||
B5_mofe_mlp,3407,all_modalities_20,0.40958791208791206,0.5904120879120879,0.8837504554280156,0.08867127238580723,0.22335518896579742,0.1614186316728592,0.12589122354984283,0.12545962631702423,0.09687625616788864,0.11222808808088303,0.15477190911769867
|
||||
B5_mofe_mlp,3407,text_30,0.5033791208791208,0.4966208791208791,0.77998020566234,0.07853517437100911,0.1615801304578781,0.24538777768611908,0.1755058914422989,0.08944669365882874,0.0692080482840538,0.1480167955160141,0.11085427552461624
|
||||
B5_mofe_mlp,3407,audio_30,0.5117582417582418,0.48824175824175825,0.7653189262124539,0.09217307279364398,0.2723240554332733,0.1130220890045166,0.20212848484516144,0.08758600801229477,0.13917095959186554,0.07771366834640503,0.10805478692054749
|
||||
B5_mofe_mlp,3407,vision_30,0.5117582417582418,0.48824175824175825,0.7773799776708603,0.08063130770882543,0.26250481605529785,0.21736890077590942,0.08825590461492538,0.17656537890434265,0.06769922375679016,0.07888038456439972,0.10872545838356018
|
||||
B5_mofe_mlp,3407,audio_vision_30,0.5117582417582418,0.48824175824175825,0.6151879114518624,0.36498818982177367,0.4589049518108368,0.11260678619146347,0.08762799948453903,0.08767727017402649,0.06704143434762955,0.07825901359319687,0.10788305103778839
|
||||
B5_mofe_mlp,3407,all_modalities_30,0.3557967032967033,0.6442032967032967,0.8791751773751674,0.09342907883561115,0.22755521535873413,0.16036975383758545,0.12519316375255585,0.12486399710178375,0.09638682752847672,0.11167588084936142,0.15395526587963104
|
||||
B5_mofe_mlp,2026,clean,0.5117582417582418,0.48824175824175825,0.892980397203899,0.08063130770882543,0.2621680796146393,0.13523989915847778,0.11440448462963104,0.1282719075679779,0.10990405827760696,0.12046957015991211,0.12954255938529968
|
||||
B5_mofe_mlp,2026,text_10,0.5091208791208791,0.4908791208791209,0.8566292977820127,0.08099503561407295,0.24004511535167694,0.16017793118953705,0.13224223256111145,0.11618264019489288,0.09917686879634857,0.1352321356534958,0.1169428601861
|
||||
B5_mofe_mlp,2026,audio_10,0.5117582417582418,0.48824175824175825,0.8513181092443619,0.08616061842387804,0.28532060980796814,0.12107318639755249,0.13112173974514008,0.11523441225290298,0.12272416055202484,0.1084277555346489,0.11609779298305511
|
||||
B5_mofe_mlp,2026,vision_10,0.5117582417582418,0.48824175824175825,0.8538046087080117,0.08063130770882543,0.275703102350235,0.15632730722427368,0.10242735594511032,0.14280176162719727,0.09840572625398636,0.1080247089266777,0.11630945652723312
|
||||
B5_mofe_mlp,2026,audio_vision_10,0.5117582417582418,0.48824175824175825,0.7992446529652792,0.1772063560231909,0.33916473388671875,0.12080469727516174,0.10259180516004562,0.11497309058904648,0.0985245332121849,0.10807139426469803,0.11586850136518478
|
||||
B5_mofe_mlp,2026,all_modalities_10,0.45884615384615385,0.5411538461538462,0.890664129810964,0.08400191593821099,0.2641141414642334,0.13430693745613098,0.11438830941915512,0.1279611438512802,0.10974214971065521,0.1203693225979805,0.12911845743656158
|
||||
B5_mofe_mlp,2026,text_20,0.5064560439560439,0.49354395604395607,0.8196418202446201,0.08093300786547328,0.21744248270988464,0.18586474657058716,0.15042437613010406,0.10369155555963516,0.08837979286909103,0.14998102188110352,0.10421676933765411
|
||||
B5_mofe_mlp,2026,audio_20,0.5117582417582418,0.48824175824175825,0.8139422624038224,0.0915288812540262,0.30578380823135376,0.10856158286333084,0.14610645174980164,0.1034226343035698,0.134155735373497,0.09755375236272812,0.10441582649946213
|
||||
B5_mofe_mlp,2026,vision_20,0.5117582417582418,0.48824175824175825,0.8189807529817417,0.08063130770882543,0.28755468130111694,0.17542824149131775,0.09184657037258148,0.1557445526123047,0.08823608607053757,0.0968705415725708,0.10431937873363495
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.5117582417582418,0.48824175824175825,0.7084234520060394,0.27120463817908524,0.41442573070526123,0.10667615383863449,0.09106616675853729,0.10168138891458511,0.0874401405453682,0.09591105580329895,0.10279884934425354
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.40585164835164833,0.5941483516483517,0.8838247695015665,0.08962296080687741,0.26898571848869324,0.13424904644489288,0.1132628470659256,0.12779442965984344,0.10867198556661606,0.1192564070224762,0.1277802437543869
|
||||
B5_mofe_mlp,2026,text_30,0.5032417582417582,0.49675824175824174,0.7814398465385116,0.08243257997597991,0.19258207082748413,0.21375314891338348,0.1692270040512085,0.09033004194498062,0.07751274853944778,0.16531100869178772,0.09128450602293015
|
||||
B5_mofe_mlp,2026,audio_30,0.5117582417582418,0.48824175824175825,0.7664926836291861,0.09711187459738028,0.3314794600009918,0.09291943162679672,0.1653663069009781,0.08855544030666351,0.14884275197982788,0.08355656266212463,0.08927922695875168
|
||||
B5_mofe_mlp,2026,vision_30,0.5117582417582418,0.48824175824175825,0.7769904015474858,0.08063130770882543,0.3017820417881012,0.19846147298812866,0.07910744100809097,0.17135068774223328,0.07599635422229767,0.08345004171133041,0.0898519977927208
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.5117582417582418,0.48824175824175825,0.6051323653073035,0.3765836375348937,0.49931350350379944,0.09166184812784195,0.07765422761440277,0.0873459056019783,0.07456637173891068,0.08182720094919205,0.08763010799884796
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.36043956043956044,0.6395604395604395,0.8852294042453963,0.08887195121951219,0.2681088149547577,0.1340326964855194,0.11355702579021454,0.12770922482013702,0.10893982648849487,0.11956492066383362,0.12808853387832642
|
||||
|
+49
@@ -0,0 +1,49 @@
|
||||
method,seed,condition,active_position_fraction,fallback_position_fraction,normalized_router_entropy,fraction_active_positions_max_weight_over_0p8,alpha_T_mean,alpha_A_mean,alpha_V_mean,alpha_TA_mean,alpha_TV_mean,alpha_AV_mean,alpha_TAV_mean
|
||||
B5_mofe_mlp,42,clean,0.5117582417582418,0.48824175824175825,0.8870560454827882,0.08063130770882543,0.2515257000923157,0.11152571439743042,0.07744884490966797,0.15852881968021393,0.12860679626464844,0.14914916455745697,0.1232161670923233
|
||||
B5_mofe_mlp,42,text_10,0.5092032967032967,0.4907967032967033,0.8506916726514709,0.08211491772322632,0.2304162234067917,0.13068588078022003,0.09430146962404251,0.14338572323322296,0.11664345115423203,0.17277489602565765,0.1117931678891182
|
||||
B5_mofe_mlp,42,audio_10,0.5117582417582418,0.48824175824175825,0.8449963602081583,0.08616061842387804,0.2751412093639374,0.10004748404026031,0.09071236103773117,0.1420598030090332,0.14774158596992493,0.13385255634784698,0.11044659465551376
|
||||
B5_mofe_mlp,42,vision_10,0.5117582417582418,0.48824175824175825,0.8472941162919574,0.08063130770882543,0.2735346555709839,0.1252371221780777,0.06957398355007172,0.1735313981771469,0.11499655246734619,0.13289612531661987,0.11023180931806564
|
||||
B5_mofe_mlp,42,audio_vision_10,0.5117582417582418,0.48824175824175825,0.7958907203885603,0.175434829289242,0.32850298285484314,0.10010535269975662,0.06980907171964645,0.14210578799247742,0.11540128290653229,0.1335059553384781,0.11057072132825851
|
||||
B5_mofe_mlp,42,all_modalities_10,0.4626098901098901,0.5373901098901099,0.8841173799028046,0.08432804798384702,0.2541447579860687,0.11095340549945831,0.07761403918266296,0.15777607262134552,0.1283317655324936,0.14818961918354034,0.12299200892448425
|
||||
B5_mofe_mlp,42,text_20,0.5065384615384615,0.49346153846153845,0.8152469884580759,0.08005206638464042,0.20999735593795776,0.14806155860424042,0.112088643014431,0.12878893315792084,0.10419154912233353,0.19696328043937683,0.09990917891263962
|
||||
B5_mofe_mlp,42,audio_20,0.5117582417582418,0.48824175824175825,0.8069851130815402,0.09013313291818767,0.2962163984775543,0.0896897166967392,0.10295859724283218,0.1273450255393982,0.16525308787822723,0.11975577473640442,0.09878180921077728
|
||||
B5_mofe_mlp,42,vision_20,0.5117582417582418,0.48824175824175825,0.8111495627938943,0.08063130770882543,0.2933293581008911,0.13767293095588684,0.062129102647304535,0.18726874887943268,0.10258819162845612,0.1186119019985199,0.09839928895235062
|
||||
B5_mofe_mlp,42,audio_vision_20,0.5117582417582418,0.48824175824175825,0.7057799858331233,0.2687352372772171,0.40449970960617065,0.08882029354572296,0.06192621961236,0.12605853378772736,0.10232582688331604,0.11834055930376053,0.09802991151809692
|
||||
B5_mofe_mlp,42,all_modalities_20,0.41145604395604396,0.588543956043956,0.8795920971657628,0.08853575482406356,0.25787994265556335,0.11065426468849182,0.07723148167133331,0.157210573554039,0.12760961055755615,0.14714252948760986,0.12227214872837067
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||||
B5_mofe_mlp,42,text_30,0.5034615384615385,0.49653846153846154,0.7845061109572483,0.07726727054458146,0.19043782353401184,0.164101243019104,0.12816408276557922,0.11582792550325394,0.0932326465845108,0.218837708234787,0.08939971774816513
|
||||
B5_mofe_mlp,42,audio_30,0.5117582417582418,0.48824175824175825,0.7627258720846881,0.09308567747476916,0.32027310132980347,0.0778515487909317,0.11745958030223846,0.11037490516901016,0.18614806234836578,0.10296247154474258,0.08493035286664963
|
||||
B5_mofe_mlp,42,vision_30,0.5117582417582418,0.48824175824175825,0.7764460734868434,0.08063130770882543,0.31232842803001404,0.1496150940656662,0.054964445531368256,0.20050112903118134,0.09068562090396881,0.10487580299377441,0.0870303362607956
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||||
B5_mofe_mlp,42,audio_vision_30,0.5117582417582418,0.48824175824175825,0.6149186646941948,0.3631092978312218,0.4812489449977875,0.07732704281806946,0.05401867628097534,0.10968495160341263,0.0891624167561531,0.10309218615293503,0.08546625822782516
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||||
B5_mofe_mlp,42,all_modalities_30,0.3595054945054945,0.6404945054945055,0.8745368649815657,0.09307657038055937,0.26191991567611694,0.11035662144422531,0.07678450644016266,0.1566968709230423,0.12672796845436096,0.14605894684791565,0.12145592272281647
|
||||
B5_mofe_mlp,3407,clean,0.5117582417582418,0.48824175824175825,0.8917789142359226,0.08063130770882543,0.21564963459968567,0.16335873305797577,0.12684088945388794,0.1254868507385254,0.09765232354402542,0.11325515806674957,0.15775780379772186
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||||
B5_mofe_mlp,3407,text_10,0.509010989010989,0.490989010989011,0.8547805451037497,0.08031088082901554,0.19791889190673828,0.1904035061597824,0.1427920013666153,0.11356116831302643,0.08846957981586456,0.12491724640130997,0.14193856716156006
|
||||
B5_mofe_mlp,3407,audio_10,0.5117582417582418,0.48824175824175825,0.8504781823179828,0.08481855271634099,0.23455235362052917,0.1466052234172821,0.15115498006343842,0.11315018683671951,0.1112954393029213,0.10172916203737259,0.14151319861412048
|
||||
B5_mofe_mlp,3407,vision_10,0.5117582417582418,0.48824175824175825,0.8539108633297741,0.08063130770882543,0.2311594933271408,0.1815430223941803,0.11412636935710907,0.1422722488641739,0.08770900219678879,0.10201089829206467,0.14117981493473053
|
||||
B5_mofe_mlp,3407,audio_vision_10,0.5117582417582418,0.48824175824175825,0.7997980860345286,0.175434829289242,0.29687586426734924,0.14598697423934937,0.11404559761285782,0.11318352073431015,0.08737359195947647,0.10181976109743118,0.14071525633335114
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||||
B5_mofe_mlp,3407,all_modalities_10,0.4610164835164835,0.5389835164835165,0.8892426095830844,0.08348727727787379,0.2185969352722168,0.16224151849746704,0.12673969566822052,0.12583576142787933,0.09755325317382812,0.11298926174640656,0.1560446321964264
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||||
B5_mofe_mlp,3407,text_20,0.5066758241758241,0.4933241758241758,0.8130542021789052,0.08176543946212655,0.17931020259857178,0.2202228158712387,0.16002467274665833,0.10018529742956161,0.07809362560510635,0.137038454413414,0.12512563169002533
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||||
B5_mofe_mlp,3407,audio_20,0.5117582417582418,0.48824175824175825,0.8087283495175436,0.09002576766158471,0.2538429796695709,0.12989234924316406,0.1755901426076889,0.10037955641746521,0.12468340992927551,0.09022346138954163,0.12538877129554749
|
||||
B5_mofe_mlp,3407,vision_20,0.5117582417582418,0.48824175824175825,0.8141886106137566,0.08063130770882543,0.24743759632110596,0.20013628900051117,0.10070110112428665,0.16005626320838928,0.0773327648639679,0.09001021832227707,0.12432596832513809
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||||
B5_mofe_mlp,3407,audio_vision_20,0.5117582417582418,0.48824175824175825,0.6969105807199653,0.28124328967146234,0.3873015344142914,0.1272396296262741,0.09933283925056458,0.09888661652803421,0.07606082409620285,0.08873630315065384,0.12244285643100739
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||||
B5_mofe_mlp,3407,all_modalities_20,0.40958791208791206,0.5904120879120879,0.8837504554280156,0.08867127238580723,0.22335518896579742,0.1614186316728592,0.12589122354984283,0.12545962631702423,0.09687625616788864,0.11222808808088303,0.15477190911769867
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||||
B5_mofe_mlp,3407,text_30,0.5033791208791208,0.4966208791208791,0.77998020566234,0.07853517437100911,0.1615801304578781,0.24538777768611908,0.1755058914422989,0.08944669365882874,0.0692080482840538,0.1480167955160141,0.11085427552461624
|
||||
B5_mofe_mlp,3407,audio_30,0.5117582417582418,0.48824175824175825,0.7653189262124539,0.09217307279364398,0.2723240554332733,0.1130220890045166,0.20212848484516144,0.08758600801229477,0.13917095959186554,0.07771366834640503,0.10805478692054749
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||||
B5_mofe_mlp,3407,vision_30,0.5117582417582418,0.48824175824175825,0.7773799776708603,0.08063130770882543,0.26250481605529785,0.21736890077590942,0.08825590461492538,0.17656537890434265,0.06769922375679016,0.07888038456439972,0.10872545838356018
|
||||
B5_mofe_mlp,3407,audio_vision_30,0.5117582417582418,0.48824175824175825,0.6151879114518624,0.36498818982177367,0.4589049518108368,0.11260678619146347,0.08762799948453903,0.08767727017402649,0.06704143434762955,0.07825901359319687,0.10788305103778839
|
||||
B5_mofe_mlp,3407,all_modalities_30,0.3557967032967033,0.6442032967032967,0.8791751773751674,0.09342907883561115,0.22755521535873413,0.16036975383758545,0.12519316375255585,0.12486399710178375,0.09638682752847672,0.11167588084936142,0.15395526587963104
|
||||
B5_mofe_mlp,2026,clean,0.5117582417582418,0.48824175824175825,0.892980397203899,0.08063130770882543,0.2621680796146393,0.13523989915847778,0.11440448462963104,0.1282719075679779,0.10990405827760696,0.12046957015991211,0.12954255938529968
|
||||
B5_mofe_mlp,2026,text_10,0.5091208791208791,0.4908791208791209,0.8566292977820127,0.08099503561407295,0.24004511535167694,0.16017793118953705,0.13224223256111145,0.11618264019489288,0.09917686879634857,0.1352321356534958,0.1169428601861
|
||||
B5_mofe_mlp,2026,audio_10,0.5117582417582418,0.48824175824175825,0.8513181092443619,0.08616061842387804,0.28532060980796814,0.12107318639755249,0.13112173974514008,0.11523441225290298,0.12272416055202484,0.1084277555346489,0.11609779298305511
|
||||
B5_mofe_mlp,2026,vision_10,0.5117582417582418,0.48824175824175825,0.8538046087080117,0.08063130770882543,0.275703102350235,0.15632730722427368,0.10242735594511032,0.14280176162719727,0.09840572625398636,0.1080247089266777,0.11630945652723312
|
||||
B5_mofe_mlp,2026,audio_vision_10,0.5117582417582418,0.48824175824175825,0.7992446529652792,0.1772063560231909,0.33916473388671875,0.12080469727516174,0.10259180516004562,0.11497309058904648,0.0985245332121849,0.10807139426469803,0.11586850136518478
|
||||
B5_mofe_mlp,2026,all_modalities_10,0.45884615384615385,0.5411538461538462,0.890664129810964,0.08400191593821099,0.2641141414642334,0.13430693745613098,0.11438830941915512,0.1279611438512802,0.10974214971065521,0.1203693225979805,0.12911845743656158
|
||||
B5_mofe_mlp,2026,text_20,0.5064560439560439,0.49354395604395607,0.8196418202446201,0.08093300786547328,0.21744248270988464,0.18586474657058716,0.15042437613010406,0.10369155555963516,0.08837979286909103,0.14998102188110352,0.10421676933765411
|
||||
B5_mofe_mlp,2026,audio_20,0.5117582417582418,0.48824175824175825,0.8139422624038224,0.0915288812540262,0.30578380823135376,0.10856158286333084,0.14610645174980164,0.1034226343035698,0.134155735373497,0.09755375236272812,0.10441582649946213
|
||||
B5_mofe_mlp,2026,vision_20,0.5117582417582418,0.48824175824175825,0.8189807529817417,0.08063130770882543,0.28755468130111694,0.17542824149131775,0.09184657037258148,0.1557445526123047,0.08823608607053757,0.0968705415725708,0.10431937873363495
|
||||
B5_mofe_mlp,2026,audio_vision_20,0.5117582417582418,0.48824175824175825,0.7084234520060394,0.27120463817908524,0.41442573070526123,0.10667615383863449,0.09106616675853729,0.10168138891458511,0.0874401405453682,0.09591105580329895,0.10279884934425354
|
||||
B5_mofe_mlp,2026,all_modalities_20,0.40585164835164833,0.5941483516483517,0.8838247695015665,0.08962296080687741,0.26898571848869324,0.13424904644489288,0.1132628470659256,0.12779442965984344,0.10867198556661606,0.1192564070224762,0.1277802437543869
|
||||
B5_mofe_mlp,2026,text_30,0.5032417582417582,0.49675824175824174,0.7814398465385116,0.08243257997597991,0.19258207082748413,0.21375314891338348,0.1692270040512085,0.09033004194498062,0.07751274853944778,0.16531100869178772,0.09128450602293015
|
||||
B5_mofe_mlp,2026,audio_30,0.5117582417582418,0.48824175824175825,0.7664926836291861,0.09711187459738028,0.3314794600009918,0.09291943162679672,0.1653663069009781,0.08855544030666351,0.14884275197982788,0.08355656266212463,0.08927922695875168
|
||||
B5_mofe_mlp,2026,vision_30,0.5117582417582418,0.48824175824175825,0.7769904015474858,0.08063130770882543,0.3017820417881012,0.19846147298812866,0.07910744100809097,0.17135068774223328,0.07599635422229767,0.08345004171133041,0.0898519977927208
|
||||
B5_mofe_mlp,2026,audio_vision_30,0.5117582417582418,0.48824175824175825,0.6051323653073035,0.3765836375348937,0.49931350350379944,0.09166184812784195,0.07765422761440277,0.0873459056019783,0.07456637173891068,0.08182720094919205,0.08763010799884796
|
||||
B5_mofe_mlp,2026,all_modalities_30,0.36043956043956044,0.6395604395604395,0.8852294042453963,0.08887195121951219,0.2681088149547577,0.1340326964855194,0.11355702579021454,0.12770922482013702,0.10893982648849487,0.11956492066383362,0.12808853387832642
|
||||
|
@@ -0,0 +1,86 @@
|
||||
{
|
||||
"experiment": "Q2 selected models: EarlyConcat + BiGRU and MoFE-7 + MLP Router",
|
||||
"created_unix": 1790272294.3490393,
|
||||
"python_version": "3.14.7 (main, Aug 10 2026, 00:00:00) [GCC 16.1.1 20260515 (Red Hat 16.1.1-2)]",
|
||||
"torch_version": "2.14.0+cu130",
|
||||
"numpy_version": "2.5.3",
|
||||
"device": "cuda",
|
||||
"cuda_device": "NVIDIA GeForce RTX 5070 Ti",
|
||||
"feature_file": "/home/gloamxun/modeling_zhaocui/E\u9898\u6570\u636e/\u9644\u4ef62-\u6570\u636e\u96c6\u7279\u5f81\u6587\u4ef6/aligned_50.pkl",
|
||||
"feature_sha256": "66e867aa74bc70a844e806e5571e371c9abb4a35f9e2887ce9b4d97ff2cb8fcd",
|
||||
"feature_dimensions": {
|
||||
"text": 768,
|
||||
"audio": 74,
|
||||
"vision": 35
|
||||
},
|
||||
"sequence_length": 50,
|
||||
"representation_note": "official ordered 50-wordpiece positions; not 50 physical-time bins",
|
||||
"train_examples": 3395,
|
||||
"valid_examples": 728,
|
||||
"train_source_video_groups": 1528,
|
||||
"valid_source_video_groups": 239,
|
||||
"train_only_scaler": "/home/gloamxun/modeling_zhaocui/deep_learning/Q2/outputs/followups/R01_selected_model_reevaluation/aligned_robust_stats.npz",
|
||||
"scaler_max_abs_difference_from_reference": 0.0,
|
||||
"test_labels_used": false,
|
||||
"seeds": [
|
||||
42,
|
||||
3407,
|
||||
2026
|
||||
],
|
||||
"epochs_max": 32,
|
||||
"patience": 6,
|
||||
"batch_size": 64,
|
||||
"optimizer": "AdamW(lr=1.5e-4, weight_decay=1e-4), gradient clip 1.0",
|
||||
"training_mask_augmentation": "same contiguous-block augment_masks protocol for both models",
|
||||
"validation_conditions": [
|
||||
"clean",
|
||||
"text_10",
|
||||
"audio_10",
|
||||
"vision_10",
|
||||
"audio_vision_10",
|
||||
"all_modalities_10",
|
||||
"text_20",
|
||||
"audio_20",
|
||||
"vision_20",
|
||||
"audio_vision_20",
|
||||
"all_modalities_20",
|
||||
"text_30",
|
||||
"audio_30",
|
||||
"vision_30",
|
||||
"audio_vision_30",
|
||||
"all_modalities_30"
|
||||
],
|
||||
"validation_corruption_seed": "seed + 13 + pattern_index*101 + int(rate*1000)",
|
||||
"loss": "cross_entropy + 0.5*SmoothL1(intensity/3, regression_label/3)",
|
||||
"models": {
|
||||
"B0_early_concat": "project modalities independently, concatenate features and masks, then BiGRU",
|
||||
"B5_mofe_mlp": {
|
||||
"experts": [
|
||||
"T",
|
||||
"A",
|
||||
"V",
|
||||
"TA",
|
||||
"TV",
|
||||
"AV",
|
||||
"TAV"
|
||||
],
|
||||
"router": "MLP over per-position observed values and local observation statistics",
|
||||
"availability": "hard mask; unavailable expert weights are zero",
|
||||
"shared_temporal_backbone": "one BiGRU after position-wise expert mixture"
|
||||
}
|
||||
},
|
||||
"best_epochs": {
|
||||
"B0_early_concat_seed_42": 4,
|
||||
"B5_mofe_mlp_seed_42": 4,
|
||||
"B0_early_concat_seed_3407": 4,
|
||||
"B5_mofe_mlp_seed_3407": 4,
|
||||
"B0_early_concat_seed_2026": 3,
|
||||
"B5_mofe_mlp_seed_2026": 4
|
||||
},
|
||||
"paired_bootstrap": {
|
||||
"replicates": 1000,
|
||||
"seed": 20260924,
|
||||
"resampling_unit": "source video id",
|
||||
"paired": true
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,3 @@
|
||||
method,n_seeds,worst_condition,clean_accuracy,clean_accuracy_sd,corrupt_accuracy_mean,corrupt_accuracy_sd,clean_macro_f1,clean_macro_f1_sd,corrupt_macro_f1_mean,corrupt_macro_f1_sd,clean_mae,clean_mae_sd,corrupt_mae_mean,corrupt_mae_sd,clean_pearson,clean_pearson_sd,corrupt_pearson_mean,corrupt_pearson_sd,worst_condition_macro_f1,worst_single_run_macro_f1,text_30_macro_f1,text_30_macro_f1_sd,audio_30_macro_f1,audio_30_macro_f1_sd,vision_30_macro_f1,vision_30_macro_f1_sd,audio_vision_30_macro_f1,audio_vision_30_macro_f1_sd,all_modalities_30_macro_f1,all_modalities_30_macro_f1_sd,corrupt_macro_f1,corrupt_mae,corrupt_pearson
|
||||
B0_early_concat,3,text_30,0.6259157509157509,0.012689016905266455,0.6226800976800976,0.011084117339613314,0.5803030257575643,0.01849482950112713,0.5751264735191365,0.016846851540436875,0.6362011035283407,0.0035474183737517766,0.6402280926704407,0.004374266641036123,0.6131094329543634,0.003049326453361512,0.6068152013123896,0.004485339859543551,0.5467200505506405,0.5160231153138954,0.5467200505506405,0.02702334845391397,0.5898777795190231,0.01981725011325887,0.5768267974155946,0.018051809113621656,0.5899580041649785,0.021659392511569595,0.5702146248141552,0.01810847481514832,0.5751264735191365,0.6402280926704407,0.6068152013123896
|
||||
B5_mofe_mlp,3,text_30,0.6405677655677655,0.011682555697960713,0.6341575091575092,0.008260560563259616,0.6078097938180046,0.012936809470245413,0.5996814814915562,0.009482724136440013,0.6383468906084696,0.01912445943818777,0.6405956546465555,0.018861146501817867,0.61092448719973,0.006638694954493296,0.6049016762167468,0.007374674358633282,0.5698233578745228,0.5665382052109811,0.5698233578745228,0.003414574297503367,0.6023602104251015,0.008745543947786412,0.6006238965304852,0.009937909445226123,0.6083796876372073,0.012980777465454897,0.5944800671676608,0.01638613384398019,0.5996814814915562,0.6405956546465555,0.6049016762167468
|
||||
|
+25
@@ -0,0 +1,25 @@
|
||||
method,seed,mask_mode,aurc_mae,rates_realized
|
||||
B0_early_concat,42,single,0.6401313925363663,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B0_early_concat,42,sync,0.6433302939648693,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B0_early_concat,42,partial,0.643875960390525,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B0_early_concat,42,async,0.6419499029297968,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
B0_early_concat,3407,single,0.6386396612080375,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B0_early_concat,3407,sync,0.6426227949801453,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B0_early_concat,3407,partial,0.6506563048804127,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B0_early_concat,3407,async,0.6473036061422844,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
B0_early_concat,2026,single,0.6465365400894263,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B0_early_concat,2026,sync,0.6504719890922472,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B0_early_concat,2026,partial,0.652087221009127,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B0_early_concat,2026,async,0.6503968739690713,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
B5_mofe_mlp,42,single,0.6329832291613164,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B5_mofe_mlp,42,sync,0.6325276544269155,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B5_mofe_mlp,42,partial,0.6334337662111412,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B5_mofe_mlp,42,async,0.6426767924420232,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
B5_mofe_mlp,3407,single,0.6373919322630748,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B5_mofe_mlp,3407,sync,0.6479961326945486,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B5_mofe_mlp,3407,partial,0.6479020337042737,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B5_mofe_mlp,3407,async,0.6466195743207078,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
B5_mofe_mlp,2026,single,0.6617258705000735,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B5_mofe_mlp,2026,sync,0.6610093338534158,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B5_mofe_mlp,2026,partial,0.6690499670696615,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B5_mofe_mlp,2026,async,0.6662885449740689,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
|
+5
@@ -0,0 +1,5 @@
|
||||
mode,delta_aurc_mae_mofe_minus_earlyconcat,bootstrap_ci_2p5,bootstrap_ci_97p5,bootstrap_probability_delta_lt_0,replicates,resampling_unit,paired,seed
|
||||
single,0.0022644793635447913,-0.007326506614258393,0.01085375445537662,0.307,1000,source video id,True,20260926
|
||||
sync,0.001702680979206006,-0.008553429202151783,0.011162477203288298,0.37,1000,source video id,True,20260926
|
||||
partial,0.0012554269016705755,-0.009299259915437324,0.010371210538351492,0.416,1000,source video id,True,20260926
|
||||
async,0.005311509565215755,-0.0041539559800425705,0.013656995740298614,0.149,1000,source video id,True,20260926
|
||||
|
@@ -0,0 +1,9 @@
|
||||
method,mask_mode,mean,sd_across_seeds
|
||||
B0_early_concat,single,0.6417691979446101,0.004195471240907912
|
||||
B0_early_concat,sync,0.6454750260124206,0.004341931450312084
|
||||
B0_early_concat,partial,0.6488731620933549,0.004386444902871605
|
||||
B0_early_concat,async,0.6465501276803842,0.004273596527398931
|
||||
B5_mofe_mlp,single,0.6440336773081549,0.015479646013878707
|
||||
B5_mofe_mlp,sync,0.6471777069916266,0.014258467000764302
|
||||
B5_mofe_mlp,partial,0.6501285889950255,0.01791219144174424
|
||||
B5_mofe_mlp,async,0.6518616372456,0.012648641515595156
|
||||
|
+253
@@ -0,0 +1,253 @@
|
||||
method,seed,scenario,realized_additional_global_rate,n_valid,accuracy,macro_f1,mae,rmse,pearson
|
||||
B0_early_concat,42,0.0/none,0.0,728,0.6332417582417582,0.587941053090477,0.6350555419921875,0.8411936357612951,0.6157338827731829
|
||||
B0_early_concat,42,0.1/single,0.03371342897433643,728,0.6304945054945055,0.5841478555667776,0.6329803466796875,0.8388883612450743,0.6156007751289291
|
||||
B0_early_concat,42,0.1/sync,0.045156406674301666,728,0.6277472527472527,0.5817500837463079,0.6324868202209473,0.8354757584548449,0.6182538400699824
|
||||
B0_early_concat,42,0.1/partial,0.040239075593981495,728,0.6291208791208791,0.5809513824305218,0.6362647414207458,0.8395663845790533,0.6146226232321855
|
||||
B0_early_concat,42,0.1/async,0.042147033495012594,728,0.6304945054945055,0.5813440322183995,0.6335626244544983,0.837625919668868,0.6163399508733897
|
||||
B0_early_concat,42,0.3/single,0.10101503353205936,728,0.6195054945054945,0.5675794227375214,0.640035092830658,0.8424158498015616,0.6069511611336497
|
||||
B0_early_concat,42,0.3/sync,0.15049590345982738,728,0.6263736263736264,0.5780608118498217,0.6299555897712708,0.8375190319916388,0.6124431874344702
|
||||
B0_early_concat,42,0.3/partial,0.11254067775371336,728,0.6153846153846154,0.5593362859645706,0.641963541507721,0.8404494474527319,0.6049209455061247
|
||||
B0_early_concat,42,0.3/async,0.1402331971734938,728,0.6318681318681318,0.576909502145226,0.6313087344169617,0.8365481276590316,0.6093167943618667
|
||||
B0_early_concat,42,0.5/single,0.16749406682715026,728,0.6291208791208791,0.5812458325756198,0.6444581151008606,0.8504945900849837,0.595658614323956
|
||||
B0_early_concat,42,0.5/sync,0.2869043063014706,728,0.6126373626373627,0.5593171296296297,0.6449117064476013,0.8485519317960112,0.5940501662945247
|
||||
B0_early_concat,42,0.5/partial,0.19417960020144912,728,0.6112637362637363,0.5538751092290113,0.6426721215248108,0.846240606269933,0.5907667712241222
|
||||
B0_early_concat,42,0.5/async,0.2674778555592227,728,0.6016483516483516,0.5399077899607511,0.6515048742294312,0.8615156389124333,0.5754295119229905
|
||||
B0_early_concat,42,0.7/single,0.233161167473855,728,0.625,0.5688829757001009,0.6452269554138184,0.8590691802596665,0.5839596403467362
|
||||
B0_early_concat,42,0.7/sync,0.4688425032750801,728,0.6016483516483516,0.5502346950183244,0.66935795545578,0.8879573422702182,0.5454190465035358
|
||||
B0_early_concat,42,0.7/partial,0.3517369377138981,728,0.6016483516483516,0.5386532608428335,0.6552613377571106,0.8613171911951291,0.5706160481156233
|
||||
B0_early_concat,42,0.7/async,0.43688540417216304,728,0.6057692307692307,0.5448128152476447,0.6480301022529602,0.8642782952419213,0.5654181079796473
|
||||
B0_early_concat,42,0.3/modality_T,0.05864506749840218,728,0.625,0.5763071383484074,0.6379959583282471,0.8473427188282466,0.5955566859385917
|
||||
B0_early_concat,42,0.3/modality_A,0.05697909847839254,728,0.6401098901098901,0.5987085232857344,0.6355111002922058,0.8415443767490056,0.6168384537396358
|
||||
B0_early_concat,42,0.3/modality_V,0.05703409792921816,728,0.6304945054945055,0.5826704686319633,0.6378379464149475,0.8427720583730931,0.6139202299259341
|
||||
B0_early_concat,42,0.3/modality_TA,0.10919187418833474,728,0.6195054945054945,0.5673255633255633,0.6411880850791931,0.8501693809265032,0.593141387871954
|
||||
B0_early_concat,42,0.3/modality_TV,0.11437644408481795,728,0.6181318681318682,0.5667943482947192,0.6455541849136353,0.8531380173804407,0.5879106305784599
|
||||
B0_early_concat,42,0.3/modality_AV,0.11303721690563862,728,0.6332417582417582,0.589575000050125,0.6335181593894958,0.8394406082973969,0.6190294231457893
|
||||
B0_early_concat,42,0.3/modality_TAV,0.16956369042443203,728,0.625,0.5736949459376823,0.636223316192627,0.8385192007210537,0.6136927230613016
|
||||
B0_early_concat,42,0.3/location_start_T,0.10048832030833439,728,0.614010989010989,0.5486629805996582,0.639001727104187,0.8471883018318189,0.5899140511730886
|
||||
B0_early_concat,42,0.3/location_middle_T,0.10048832030833439,728,0.6195054945054945,0.5621330833277529,0.6401935815811157,0.8398970121305769,0.6011036539570971
|
||||
B0_early_concat,42,0.3/location_end_T,0.10048832030833439,728,0.6167582417582418,0.558781569307885,0.6448237895965576,0.8462808587041787,0.595287414298351
|
||||
B0_early_concat,42,0.3/span_long_T,0.10048832030833439,728,0.6167582417582418,0.5587239725548967,0.6371496915817261,0.8397095329026115,0.5977651886958409
|
||||
B0_early_concat,42,0.3/span_multi_short_T,0.10048832030833439,728,0.6167582417582418,0.5618207578802662,0.6346496939659119,0.8382192825209313,0.5993613309755399
|
||||
B0_early_concat,42,0.3/location_start_A,0.10087109490306286,728,0.635989010989011,0.5935620701417008,0.6319957971572876,0.84067373737167,0.6193052962176031
|
||||
B0_early_concat,42,0.3/location_middle_A,0.10087109490306286,728,0.6304945054945055,0.5891673048189151,0.6320388317108154,0.8388446986922057,0.6193795942976837
|
||||
B0_early_concat,42,0.3/location_end_A,0.10087109490306286,728,0.6304945054945055,0.5891673048189151,0.6308991312980652,0.8360611654771293,0.6216326232820929
|
||||
B0_early_concat,42,0.3/span_long_A,0.10087109490306286,728,0.6304945054945055,0.586797819903155,0.6292437314987183,0.8373133664919333,0.6218214161352669
|
||||
B0_early_concat,42,0.3/span_multi_short_A,0.10087109490306286,728,0.6332417582417582,0.5918991467740389,0.6312629580497742,0.8393302944773211,0.620064068130471
|
||||
B0_early_concat,42,0.3/location_start_V,0.09701596125937247,728,0.6373626373626373,0.5909589685370776,0.638043999671936,0.8432465570143738,0.6133269596558762
|
||||
B0_early_concat,42,0.3/location_middle_V,0.09701596125937247,728,0.6291208791208791,0.5802229949228151,0.636878252029419,0.8422387328692155,0.6142276235341132
|
||||
B0_early_concat,42,0.3/location_end_V,0.09701596125937247,728,0.6291208791208791,0.5802229949228151,0.6369577050209045,0.8424747861717187,0.6139934605500105
|
||||
B0_early_concat,42,0.3/span_long_V,0.09701596125937247,728,0.6304945054945055,0.583777087861221,0.6353855133056641,0.8398962669808279,0.6167031708983985
|
||||
B0_early_concat,42,0.3/span_multi_short_V,0.09701596125937247,728,0.6304945054945055,0.5833277915350489,0.6393547654151917,0.8443521540873805,0.6124599424438969
|
||||
B0_early_concat,42,0.3/synchrony_sync,0.17627119309968198,728,0.6236263736263736,0.5712425532056137,0.6429818272590637,0.8454751991613966,0.6058335119911614
|
||||
B0_early_concat,42,0.3/synchrony_partial,0.11943882005826376,728,0.6304945054945055,0.5832748099288496,0.6332861185073853,0.8400844140439543,0.6035583549739136
|
||||
B0_early_concat,42,0.3/synchrony_async,0.16594815654028122,728,0.6332417582417582,0.581960911374582,0.634742021560669,0.8411228109856493,0.6030323439352911
|
||||
B0_early_concat,3407,0.0/none,0.0,728,0.6332417582417582,0.5937554950072336,0.6333680152893066,0.8346194991301408,0.6138300851146614
|
||||
B0_early_concat,3407,0.1/single,0.03371342897433643,728,0.6277472527472527,0.5863431107430745,0.6328662633895874,0.8353187909586893,0.6112280473426515
|
||||
B0_early_concat,3407,0.1/sync,0.045156406674301666,728,0.6263736263736264,0.5838823759644308,0.6331413984298706,0.8319518002110763,0.614769736946681
|
||||
B0_early_concat,3407,0.1/partial,0.040239075593981495,728,0.6277472527472527,0.5826595399578411,0.6362914443016052,0.8349912760615754,0.6108295560922031
|
||||
B0_early_concat,3407,0.1/async,0.042147033495012594,728,0.6401098901098901,0.5984721457021069,0.6350982785224915,0.8343727940448075,0.6137234888279289
|
||||
B0_early_concat,3407,0.3/single,0.10101503353205936,728,0.6085164835164835,0.563921331484755,0.6361177563667297,0.8353053046479242,0.607661728262342
|
||||
B0_early_concat,3407,0.3/sync,0.15049590345982738,728,0.6304945054945055,0.5883092160267541,0.6361386775970459,0.8404312208242788,0.6029838091344039
|
||||
B0_early_concat,3407,0.3/partial,0.11254067775371336,728,0.6112637362637363,0.5649195311816672,0.642254650592804,0.8373105190635507,0.6025399956015483
|
||||
B0_early_concat,3407,0.3/async,0.1402331971734938,728,0.6236263736263736,0.5729838717006412,0.6402410268783569,0.8337487059759023,0.6076096623115538
|
||||
B0_early_concat,3407,0.5/single,0.16749406682715026,728,0.6181318681318682,0.5715556497676894,0.6397385597229004,0.8471463687132873,0.5913795821530734
|
||||
B0_early_concat,3407,0.5/sync,0.2869043063014706,728,0.6236263736263736,0.575541941133339,0.6427107453346252,0.8423896702594076,0.5942984252907214
|
||||
B0_early_concat,3407,0.5/partial,0.19417960020144912,728,0.5961538461538461,0.5415150811859474,0.6579906940460205,0.8591292636831587,0.5722431967077758
|
||||
B0_early_concat,3407,0.5/async,0.2674778555592227,728,0.603021978021978,0.5529601029601029,0.6514623165130615,0.8635603164542541,0.5680182640279093
|
||||
B0_early_concat,3407,0.7/single,0.233161167473855,728,0.603021978021978,0.5548110166904493,0.653153657913208,0.864040575904769,0.5720059484103266
|
||||
B0_early_concat,3407,0.7/sync,0.4688425032750801,728,0.6071428571428571,0.5592133635943569,0.6612244248390198,0.8699659907610593,0.5613123004112319
|
||||
B0_early_concat,3407,0.7/partial,0.3517369377138981,728,0.5782967032967034,0.5192448487580333,0.6624062657356262,0.8770518088093162,0.5473815485219784
|
||||
B0_early_concat,3407,0.7/async,0.43688540417216304,728,0.5782967032967034,0.5296829018983362,0.6629856824874878,0.8789931529844939,0.5433830120722912
|
||||
B0_early_concat,3407,0.3/modality_T,0.05864506749840218,728,0.6167582417582418,0.5696594236400062,0.6442276835441589,0.8481597459797712,0.5886136769457235
|
||||
B0_early_concat,3407,0.3/modality_A,0.05697909847839254,728,0.6332417582417582,0.5935566473770096,0.6333451867103577,0.8344743705182801,0.6155545899116962
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||||
B0_early_concat,3407,0.3/modality_V,0.05703409792921816,728,0.6332417582417582,0.5934148419250151,0.6332776546478271,0.8344196193351635,0.6139845146475589
|
||||
B0_early_concat,3407,0.3/modality_TA,0.10919187418833474,728,0.6167582417582418,0.569608407866905,0.6469659209251404,0.8517946749213303,0.5848663158386197
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||||
B0_early_concat,3407,0.3/modality_TV,0.11437644408481795,728,0.6057692307692307,0.5520132224603463,0.6410850882530212,0.8440129965170219,0.5908302231341378
|
||||
B0_early_concat,3407,0.3/modality_AV,0.11303721690563862,728,0.635989010989011,0.5984543253270477,0.6292101740837097,0.8312502136803833,0.6188758147944096
|
||||
B0_early_concat,3407,0.3/modality_TAV,0.16956369042443203,728,0.6222527472527473,0.577255329165107,0.6411339044570923,0.8406993677079958,0.6056894215716182
|
||||
B0_early_concat,3407,0.3/location_start_T,0.10048832030833439,728,0.6167582417582418,0.5616277516526954,0.6559486985206604,0.854438684150858,0.5788422305236482
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B0_early_concat,3407,0.3/location_middle_T,0.10048832030833439,728,0.6071428571428571,0.547740563024856,0.6456643342971802,0.8450714289366523,0.59239383541254
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B0_early_concat,3407,0.3/location_end_T,0.10048832030833439,728,0.6071428571428571,0.5468314040316676,0.6502484083175659,0.8484889919328977,0.5891420561980362
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B0_early_concat,3407,0.3/span_long_T,0.10048832030833439,728,0.6016483516483516,0.546928522672282,0.6454964280128479,0.8463376948392111,0.5878408095083768
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B0_early_concat,3407,0.3/span_multi_short_T,0.10048832030833439,728,0.6043956043956044,0.5515248320550723,0.6477841138839722,0.8459924639012224,0.5877258960827487
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B0_early_concat,3407,0.3/location_start_A,0.10087109490306286,728,0.6263736263736264,0.5891968004925136,0.63096684217453,0.8328749627885234,0.618139931953556
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B0_early_concat,3407,0.3/location_middle_A,0.10087109490306286,728,0.6373626373626373,0.5982533903882219,0.6332005262374878,0.8344721205404403,0.6156531655487061
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B0_early_concat,3407,0.3/location_end_A,0.10087109490306286,728,0.6401098901098901,0.6003231457093513,0.6325213313102722,0.8332261294709254,0.6168599173095554
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B0_early_concat,3407,0.3/span_long_A,0.10087109490306286,728,0.6304945054945055,0.5918206496100208,0.6307344436645508,0.8312857068072388,0.6198440817316815
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B0_early_concat,3407,0.3/span_multi_short_A,0.10087109490306286,728,0.6332417582417582,0.595786573091332,0.6304507851600647,0.8323247687322188,0.6185376730913125
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B0_early_concat,3407,0.3/location_start_V,0.09701596125937247,728,0.6318681318681318,0.5918186769129088,0.6308284997940063,0.8326575559153797,0.6164779072814917
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B0_early_concat,3407,0.3/location_middle_V,0.09701596125937247,728,0.6318681318681318,0.5930726844490408,0.6334424018859863,0.835375730759368,0.6128703835769779
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B0_early_concat,3407,0.3/location_end_V,0.09701596125937247,728,0.6304945054945055,0.5915655585223337,0.6334879398345947,0.835227415159139,0.6128021593800222
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B0_early_concat,3407,0.3/span_long_V,0.09701596125937247,728,0.6346153846153846,0.5958501672120969,0.6301674246788025,0.832417931048369,0.6161365463499257
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B0_early_concat,3407,0.3/span_multi_short_V,0.09701596125937247,728,0.6291208791208791,0.588772574029934,0.6311795711517334,0.833889672220184,0.6149213762305303
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B0_early_concat,3407,0.3/synchrony_sync,0.17627119309968198,728,0.6304945054945055,0.5874171274320514,0.6434048414230347,0.8416043656648424,0.6052197775255865
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B0_early_concat,3407,0.3/synchrony_partial,0.11943882005826376,728,0.6153846153846154,0.5725142421088963,0.638130247592926,0.8434438856574996,0.5938085222353164
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B0_early_concat,3407,0.3/synchrony_async,0.16594815654028122,728,0.6263736263736264,0.5815558788981249,0.639380156993866,0.8382507475096762,0.601474525688235
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B0_early_concat,2026,0.0/none,0.0,728,0.6112637362637363,0.5592125291749822,0.6401797533035278,0.8435639776807761,0.6097643309752457
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B0_early_concat,2026,0.1/single,0.03371342897433643,728,0.6126373626373627,0.5601732347712779,0.6388869881629944,0.8425065874583629,0.6090522004630045
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B0_early_concat,2026,0.1/sync,0.045156406674301666,728,0.6208791208791209,0.5649448309789866,0.6389307975769043,0.8412108184623058,0.6108543782865608
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B0_early_concat,2026,0.1/partial,0.040239075593981495,728,0.614010989010989,0.5584513367819262,0.6431105732917786,0.8447519993121942,0.6059585962909831
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B0_early_concat,2026,0.1/async,0.042147033495012594,728,0.614010989010989,0.5589535709422427,0.6394624710083008,0.8424333613384806,0.6086355218373317
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B0_early_concat,2026,0.3/single,0.10101503353205936,728,0.5961538461538461,0.5303411844263911,0.644254207611084,0.8467073887008049,0.6011147024802118
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B0_early_concat,2026,0.3/sync,0.15049590345982738,728,0.6153846153846154,0.5586649169024365,0.6396176815032959,0.8460189546756811,0.6038839691724569
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B0_early_concat,2026,0.3/partial,0.11254067775371336,728,0.6002747252747253,0.5414842809750425,0.6449089646339417,0.8454197856067814,0.6000672714828029
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B0_early_concat,2026,0.3/async,0.1402331971734938,728,0.6167582417582418,0.5574463118580766,0.6412432193756104,0.8442993142001068,0.6000500422354057
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B0_early_concat,2026,0.5/single,0.16749406682715026,728,0.5906593406593407,0.5343478616835018,0.6554132699966431,0.8629948412784115,0.5779273255314922
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B0_early_concat,2026,0.5/sync,0.2869043063014706,728,0.6057692307692307,0.5402298406725984,0.6494545936584473,0.8566324340595707,0.5939648586438693
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B0_early_concat,2026,0.5/partial,0.19417960020144912,728,0.5892857142857143,0.5226659187505066,0.6543736457824707,0.8614206069809918,0.5773399814562676
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B0_early_concat,2026,0.5/async,0.2674778555592227,728,0.5934065934065934,0.5295882956865473,0.6541514992713928,0.8724610071841917,0.5626896612214186
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B0_early_concat,2026,0.7/single,0.233161167473855,728,0.5934065934065934,0.532628227109786,0.6483538150787354,0.870265481387598,0.5673644852821225
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B0_early_concat,2026,0.7/sync,0.4688425032750801,728,0.5961538461538461,0.5301148286882755,0.6787758469581604,0.8906546470660056,0.547949008886643
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B0_early_concat,2026,0.7/partial,0.3517369377138981,728,0.5782967032967034,0.49990870782827085,0.6650825142860413,0.8827671950876751,0.5543444352742108
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B0_early_concat,2026,0.7/async,0.43688540417216304,728,0.5714285714285714,0.5025610545542795,0.6675907373428345,0.8872400843457747,0.5422344198391074
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B0_early_concat,2026,0.3/modality_T,0.05864506749840218,728,0.5947802197802198,0.5351898961754573,0.6460724472999573,0.8546291394157867,0.5876677547086017
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B0_early_concat,2026,0.3/modality_A,0.05697909847839254,728,0.6167582417582418,0.5662772023588923,0.6368343830108643,0.8410307546655318,0.6118634446955162
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B0_early_concat,2026,0.3/modality_V,0.05703409792921816,728,0.6126373626373627,0.557729972907977,0.6418033838272095,0.8440729159094172,0.6100584181871076
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B0_early_concat,2026,0.3/modality_TA,0.10919187418833474,728,0.603021978021978,0.5448842919697842,0.6518500447273254,0.8589307850717696,0.5797191740283412
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B0_early_concat,2026,0.3/modality_TV,0.11437644408481795,728,0.603021978021978,0.541860535364365,0.6528465151786804,0.8566144821832752,0.588955738533617
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B0_early_concat,2026,0.3/modality_AV,0.11303721690563862,728,0.6304945054945055,0.5825187723642906,0.6375922560691833,0.8408415788360272,0.612813220807612
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B0_early_concat,2026,0.3/modality_TAV,0.16956369042443203,728,0.6057692307692307,0.5458579640041461,0.6483514904975891,0.8455093549439832,0.608450763176158
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B0_early_concat,2026,0.3/location_start_T,0.10048832030833439,728,0.5975274725274725,0.5154262536957387,0.6474388837814331,0.8511553849841474,0.5876055423314643
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B0_early_concat,2026,0.3/location_middle_T,0.10048832030833439,728,0.5947802197802198,0.5273134273577562,0.651376485824585,0.8531833936108886,0.5919773613751391
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B0_early_concat,2026,0.3/location_end_T,0.10048832030833439,728,0.5989010989010989,0.5317455371915709,0.6568161845207214,0.8567943666389586,0.5878101230844675
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B0_early_concat,2026,0.3/span_long_T,0.10048832030833439,728,0.592032967032967,0.5220599876513855,0.6480600833892822,0.8553228036066841,0.5854352052042763
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B0_early_concat,2026,0.3/span_multi_short_T,0.10048832030833439,728,0.5906593406593407,0.5159900126701303,0.6425683498382568,0.8479485073875213,0.5947492287997942
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B0_early_concat,2026,0.3/location_start_A,0.10087109490306286,728,0.6126373626373627,0.563729128324724,0.6361474394798279,0.8418471814765383,0.6102622224288402
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B0_early_concat,2026,0.3/location_middle_A,0.10087109490306286,728,0.6153846153846154,0.5629585797451505,0.6369883418083191,0.8422769120407221,0.6104588818493184
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B0_early_concat,2026,0.3/location_end_A,0.10087109490306286,728,0.6126373626373627,0.5599234991449159,0.6361879110336304,0.8414413515665965,0.6112857790951658
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B0_early_concat,2026,0.3/span_long_A,0.10087109490306286,728,0.6181318681318682,0.5672427371505847,0.6351941227912903,0.84013680956134,0.6122003841323984
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B0_early_concat,2026,0.3/span_multi_short_A,0.10087109490306286,728,0.6126373626373627,0.5600733772344474,0.6348678469657898,0.8409436143236783,0.6113205736925018
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B0_early_concat,2026,0.3/location_start_V,0.09701596125937247,728,0.6126373626373627,0.5611197593956215,0.64106684923172,0.8454543313788724,0.6088502283110014
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B0_early_concat,2026,0.3/location_middle_V,0.09701596125937247,728,0.6085164835164835,0.5557324605271149,0.642802894115448,0.8447385930433952,0.6088194139871752
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B0_early_concat,2026,0.3/location_end_V,0.09701596125937247,728,0.6098901098901099,0.5575133773353141,0.6417749524116516,0.8442896777118307,0.6093391576059886
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B0_early_concat,2026,0.3/span_long_V,0.09701596125937247,728,0.6181318681318682,0.5667042220475478,0.6411034464836121,0.844152566453742,0.6097178840476188
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B0_early_concat,2026,0.3/span_multi_short_V,0.09701596125937247,728,0.6153846153846154,0.5651938412949072,0.642799437046051,0.845178842466505,0.6091480103515892
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B0_early_concat,2026,0.3/synchrony_sync,0.17627119309968198,728,0.6057692307692307,0.5482100254697998,0.6528782844543457,0.8552752759399308,0.5958982611163057
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B0_early_concat,2026,0.3/synchrony_partial,0.11943882005826376,728,0.6126373626373627,0.5553496423474522,0.6373363137245178,0.8448557143072355,0.5996811452037548
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B0_early_concat,2026,0.3/synchrony_async,0.16594815654028122,728,0.6208791208791209,0.5618089083713896,0.642960786819458,0.8441256287463826,0.6005135762432049
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B5_mofe_mlp,42,0.0/none,0.0,728,0.6538461538461539,0.6219292861291515,0.6228764653205872,0.8430840725364007,0.6143991595201629
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B5_mofe_mlp,42,0.1/single,0.03371342897433643,728,0.6483516483516484,0.6176568539994053,0.6194556951522827,0.8364675392287196,0.6155295037181994
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B5_mofe_mlp,42,0.1/sync,0.045156406674301666,728,0.646978021978022,0.6131089418994519,0.6230729222297668,0.8388785560201717,0.6141908451088897
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B5_mofe_mlp,42,0.1/partial,0.040239075593981495,728,0.6524725274725275,0.6193363630301347,0.6241474151611328,0.8379474256065216,0.6137031429539084
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B5_mofe_mlp,42,0.1/async,0.042147033495012594,728,0.6497252747252747,0.6159992213876729,0.6239848732948303,0.8404273555935142,0.61353036159771
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B5_mofe_mlp,42,0.3/single,0.10101503353205936,728,0.6373626373626373,0.5985146260620283,0.6270084977149963,0.8386096847780098,0.6054063180216553
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B5_mofe_mlp,42,0.3/sync,0.15049590345982738,728,0.6414835164835165,0.6040789612486607,0.6249569058418274,0.8408457611521547,0.6049185603235804
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B5_mofe_mlp,42,0.3/partial,0.11254067775371336,728,0.6304945054945055,0.5891368041469461,0.6224022507667542,0.827918548761029,0.6144819802426599
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B5_mofe_mlp,42,0.3/async,0.1402331971734938,728,0.6483516483516484,0.6074532789670405,0.6267399191856384,0.8365157435862942,0.60522919392934
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B5_mofe_mlp,42,0.5/single,0.16749406682715026,728,0.6373626373626373,0.5935685808642579,0.641523003578186,0.8501884503989168,0.5866277942269824
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B5_mofe_mlp,42,0.5/sync,0.2869043063014706,728,0.6277472527472527,0.5844696109712227,0.6337242722511292,0.8441922476966766,0.5913227359189296
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B5_mofe_mlp,42,0.5/partial,0.19417960020144912,728,0.6346153846153846,0.5872227018393876,0.6360241174697876,0.8445437900624987,0.5922147321419193
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B5_mofe_mlp,42,0.5/async,0.2674778555592227,728,0.6071428571428571,0.5548667051067803,0.6596632599830627,0.8709813887997953,0.5530374150565661
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B5_mofe_mlp,42,0.7/single,0.233161167473855,728,0.6085164835164835,0.5566056168847249,0.6539682149887085,0.8732921417971317,0.5559331721614461
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B5_mofe_mlp,42,0.7/sync,0.4688425032750801,728,0.6153846153846154,0.5722363903398882,0.6507095694541931,0.8706489761786416,0.5546201796993863
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B5_mofe_mlp,42,0.7/partial,0.3517369377138981,728,0.6112637362637363,0.5491367242946944,0.649608850479126,0.8622736163821897,0.5674264189655753
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B5_mofe_mlp,42,0.7/async,0.43688540417216304,728,0.614010989010989,0.5607072922993648,0.6545283794403076,0.8672503886745678,0.5562671204175875
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B5_mofe_mlp,42,0.3/modality_T,0.05864506749840218,728,0.6373626373626373,0.5968187892381337,0.6317851543426514,0.8464475179199263,0.6006693398835592
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B5_mofe_mlp,42,0.3/modality_A,0.05697909847839254,728,0.646978021978022,0.6163107544157121,0.6207097768783569,0.838498053196448,0.6142489597323474
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B5_mofe_mlp,42,0.3/modality_V,0.05703409792921816,728,0.6442307692307693,0.6107151863557211,0.6259862780570984,0.8335144362752684,0.6153024937943374
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B5_mofe_mlp,42,0.3/modality_TA,0.10919187418833474,728,0.6428571428571429,0.6043780415380584,0.6327931880950928,0.8475631100160345,0.5948025418510873
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B5_mofe_mlp,42,0.3/modality_TV,0.11437644408481795,728,0.6373626373626373,0.5959482244281312,0.6271441578865051,0.8361193735369933,0.6012465766270015
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B5_mofe_mlp,42,0.3/modality_AV,0.11303721690563862,728,0.657967032967033,0.6265967365967366,0.6204225420951843,0.8320528842459516,0.6142369587359615
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B5_mofe_mlp,42,0.3/modality_TAV,0.16956369042443203,728,0.6387362637362637,0.6022829403270885,0.6247004270553589,0.8415388521710019,0.6114450566462162
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B5_mofe_mlp,42,0.3/location_start_T,0.10048832030833439,728,0.6167582417582418,0.5551944119171176,0.6426858305931091,0.8588827630798264,0.5909442057230415
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B5_mofe_mlp,42,0.3/location_middle_T,0.10048832030833439,728,0.6277472527472527,0.5816861376992662,0.6292437314987183,0.8380489244291087,0.6084504680158224
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B5_mofe_mlp,42,0.3/location_end_T,0.10048832030833439,728,0.6291208791208791,0.5828384880080901,0.6327103972434998,0.8456859983335451,0.6009234012556889
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B5_mofe_mlp,42,0.3/span_long_T,0.10048832030833439,728,0.6181318681318682,0.5606029894245005,0.63385009765625,0.8449191717280062,0.5999291487943097
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B5_mofe_mlp,42,0.3/span_multi_short_T,0.10048832030833439,728,0.6236263736263736,0.5675871193351786,0.6286787390708923,0.8434076674373588,0.6027067451671214
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B5_mofe_mlp,42,0.3/location_start_A,0.10087109490306286,728,0.6497252747252747,0.6197366933833278,0.6174412965774536,0.8388514134230686,0.6113825928060521
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B5_mofe_mlp,42,0.3/location_middle_A,0.10087109490306286,728,0.646978021978022,0.6173225209844928,0.616412878036499,0.8338065393313597,0.6161370673969482
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B5_mofe_mlp,42,0.3/location_end_A,0.10087109490306286,728,0.646978021978022,0.6165553163133471,0.6158262491226196,0.8313431379297845,0.6183121117147332
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B5_mofe_mlp,42,0.3/span_long_A,0.10087109490306286,728,0.6483516483516484,0.6173720425147514,0.6175615787506104,0.8363065172492736,0.6136977910950321
|
||||
B5_mofe_mlp,42,0.3/span_multi_short_A,0.10087109490306286,728,0.6524725274725275,0.6230131272943935,0.61532062292099,0.8349310975570658,0.6150409227419862
|
||||
B5_mofe_mlp,42,0.3/location_start_V,0.09701596125937247,728,0.6442307692307693,0.6101387544638678,0.6222208738327026,0.8278320442101604,0.6172869524300535
|
||||
B5_mofe_mlp,42,0.3/location_middle_V,0.09701596125937247,728,0.6442307692307693,0.6093692166419439,0.6222869753837585,0.8253240180231957,0.6206632365514538
|
||||
B5_mofe_mlp,42,0.3/location_end_V,0.09701596125937247,728,0.6414835164835165,0.6068048524614181,0.6223054528236389,0.8262935756209701,0.619957370820794
|
||||
B5_mofe_mlp,42,0.3/span_long_V,0.09701596125937247,728,0.646978021978022,0.6112351316308698,0.622149646282196,0.8255536446935012,0.6199181054653543
|
||||
B5_mofe_mlp,42,0.3/span_multi_short_V,0.09701596125937247,728,0.6428571428571429,0.6082354427182013,0.6236581206321716,0.8262526380234242,0.6195939305316789
|
||||
B5_mofe_mlp,42,0.3/synchrony_sync,0.17627119309968198,728,0.6373626373626373,0.6012358038786352,0.6281257271766663,0.8476797355527455,0.6060950536914038
|
||||
B5_mofe_mlp,42,0.3/synchrony_partial,0.11943882005826376,728,0.6346153846153846,0.5923570448352682,0.6266241669654846,0.8353940676885147,0.6059126232533022
|
||||
B5_mofe_mlp,42,0.3/synchrony_async,0.16594815654028122,728,0.6346153846153846,0.5925850106177974,0.6234601140022278,0.8406986941683526,0.5973964270479869
|
||||
B5_mofe_mlp,3407,0.0/none,0.0,728,0.635989010989011,0.604973907499834,0.6324349641799927,0.838804657884871,0.6151046893704437
|
||||
B5_mofe_mlp,3407,0.1/single,0.03371342897433643,728,0.6373626373626373,0.6048865594071073,0.6280990242958069,0.8329202621621531,0.6151751620920511
|
||||
B5_mofe_mlp,3407,0.1/sync,0.045156406674301666,728,0.6304945054945055,0.5987230879568809,0.6321651935577393,0.8356450719141751,0.6145683643566429
|
||||
B5_mofe_mlp,3407,0.1/partial,0.040239075593981495,728,0.6332417582417582,0.598012204601852,0.6343168616294861,0.836387477516575,0.6110104686409112
|
||||
B5_mofe_mlp,3407,0.1/async,0.042147033495012594,728,0.635989010989011,0.6058945511736596,0.6329501867294312,0.8365664388900896,0.6153538223070723
|
||||
B5_mofe_mlp,3407,0.3/single,0.10101503353205936,728,0.6346153846153846,0.5990035446502852,0.6325004696846008,0.8355625773519788,0.6046990738861794
|
||||
B5_mofe_mlp,3407,0.3/sync,0.15049590345982738,728,0.6304945054945055,0.5957759196211425,0.6371961832046509,0.84088180618401,0.602958316177432
|
||||
B5_mofe_mlp,3407,0.3/partial,0.11254067775371336,728,0.6208791208791209,0.5825165271433349,0.6410707831382751,0.8389358225978112,0.598158496010818
|
||||
B5_mofe_mlp,3407,0.3/async,0.1402331971734938,728,0.6318681318681318,0.5942475648935711,0.6402276158332825,0.839390974198143,0.6007527560377187
|
||||
B5_mofe_mlp,3407,0.5/single,0.16749406682715026,728,0.6332417582417582,0.5948964744967374,0.6464778184890747,0.8446069533500644,0.5901295001763649
|
||||
B5_mofe_mlp,3407,0.5/sync,0.2869043063014706,728,0.6318681318681318,0.5973188250716287,0.6492260694503784,0.8514326854066492,0.5825697846418139
|
||||
B5_mofe_mlp,3407,0.5/partial,0.19417960020144912,728,0.6181318681318682,0.5737695892370467,0.6486934423446655,0.8496342797849444,0.5804087890235984
|
||||
B5_mofe_mlp,3407,0.5/async,0.2674778555592227,728,0.6112637362637363,0.5720071090958225,0.6490155458450317,0.8661096765277796,0.559367928353015
|
||||
B5_mofe_mlp,3407,0.7/single,0.233161167473855,728,0.5975274725274725,0.5517406725325694,0.6459130644798279,0.8581754114801059,0.5724437675509451
|
||||
B5_mofe_mlp,3407,0.7/sync,0.4688425032750801,728,0.5892857142857143,0.552859114928787,0.677151620388031,0.8907122987492757,0.531687592193011
|
||||
B5_mofe_mlp,3407,0.7/partial,0.3517369377138981,728,0.5892857142857143,0.5342811882319379,0.6670288443565369,0.8729558978373072,0.5473239468352531
|
||||
B5_mofe_mlp,3407,0.7/async,0.43688540417216304,728,0.5810439560439561,0.5320545275034573,0.6657702922821045,0.8800158807557013,0.5376864140920043
|
||||
B5_mofe_mlp,3407,0.3/modality_T,0.05864506749840218,728,0.6346153846153846,0.592395637194854,0.6376990079879761,0.8418836438274057,0.5952924527832733
|
||||
B5_mofe_mlp,3407,0.3/modality_A,0.05697909847839254,728,0.6346153846153846,0.6053242660314008,0.631351888179779,0.8380616909298862,0.6145230523563534
|
||||
B5_mofe_mlp,3407,0.3/modality_V,0.05703409792921816,728,0.6387362637362637,0.6076841472669062,0.6331720948219299,0.8356800930832423,0.610946837414197
|
||||
B5_mofe_mlp,3407,0.3/modality_TA,0.10919187418833474,728,0.6208791208791209,0.587877532835486,0.6422289609909058,0.8495119937905492,0.5922293943405987
|
||||
B5_mofe_mlp,3407,0.3/modality_TV,0.11437644408481795,728,0.6332417582417582,0.589795993553472,0.6403915286064148,0.8451140292386135,0.5883170312494674
|
||||
B5_mofe_mlp,3407,0.3/modality_AV,0.11303721690563862,728,0.6277472527472527,0.5986501178019438,0.6302677392959595,0.8346439585295746,0.6170157327095299
|
||||
B5_mofe_mlp,3407,0.3/modality_TAV,0.16956369042443203,728,0.6208791208791209,0.5872355756816936,0.6344102025032043,0.8431307321499237,0.6069219241721779
|
||||
B5_mofe_mlp,3407,0.3/location_start_T,0.10048832030833439,728,0.6208791208791209,0.5691816344789541,0.6474371552467346,0.8457314924808049,0.5877471209842607
|
||||
B5_mofe_mlp,3407,0.3/location_middle_T,0.10048832030833439,728,0.6332417582417582,0.580026202948566,0.6398654580116272,0.8329578308637743,0.602320103267925
|
||||
B5_mofe_mlp,3407,0.3/location_end_T,0.10048832030833439,728,0.6346153846153846,0.5818332297643384,0.6438518762588501,0.8348256140910719,0.6006683747918653
|
||||
B5_mofe_mlp,3407,0.3/span_long_T,0.10048832030833439,728,0.6304945054945055,0.5789449562705777,0.638378918170929,0.839944168119987,0.5929227244179269
|
||||
B5_mofe_mlp,3407,0.3/span_multi_short_T,0.10048832030833439,728,0.635989010989011,0.5830090515689985,0.6403829455375671,0.8377337542318748,0.5959436129993941
|
||||
B5_mofe_mlp,3407,0.3/location_start_A,0.10087109490306286,728,0.6222527472527473,0.5942606106743894,0.6317183375358582,0.8378718803105245,0.6163487843098526
|
||||
B5_mofe_mlp,3407,0.3/location_middle_A,0.10087109490306286,728,0.6332417582417582,0.6041073785131045,0.6293778419494629,0.8342761706281807,0.6171306545936357
|
||||
B5_mofe_mlp,3407,0.3/location_end_A,0.10087109490306286,728,0.635989010989011,0.6045352623195686,0.6293238401412964,0.8329167198828686,0.6180389298373584
|
||||
B5_mofe_mlp,3407,0.3/span_long_A,0.10087109490306286,728,0.6346153846153846,0.6060356885394697,0.6299681067466736,0.8372156941677521,0.614922712649418
|
||||
B5_mofe_mlp,3407,0.3/span_multi_short_A,0.10087109490306286,728,0.625,0.5980538669345082,0.6309807896614075,0.8373939802903236,0.6152266066983048
|
||||
B5_mofe_mlp,3407,0.3/location_start_V,0.09701596125937247,728,0.646978021978022,0.6167710620102839,0.6295149922370911,0.8281255398154749,0.6150683890220531
|
||||
B5_mofe_mlp,3407,0.3/location_middle_V,0.09701596125937247,728,0.6291208791208791,0.5970350664860342,0.6279875040054321,0.8285469923327045,0.6150038375612108
|
||||
B5_mofe_mlp,3407,0.3/location_end_V,0.09701596125937247,728,0.6291208791208791,0.5970350664860342,0.628416121006012,0.8286181007474381,0.6152751252437939
|
||||
B5_mofe_mlp,3407,0.3/span_long_V,0.09701596125937247,728,0.6346153846153846,0.6033920140660455,0.6285055875778198,0.8288092755139251,0.6145346855118451
|
||||
B5_mofe_mlp,3407,0.3/span_multi_short_V,0.09701596125937247,728,0.6373626373626373,0.6050369975450578,0.6291371583938599,0.8286749255438085,0.6143714918917834
|
||||
B5_mofe_mlp,3407,0.3/synchrony_sync,0.17627119309968198,728,0.6236263736263736,0.592557354039046,0.6403738856315613,0.8458653177750385,0.6041630287343566
|
||||
B5_mofe_mlp,3407,0.3/synchrony_partial,0.11943882005826376,728,0.6373626373626373,0.5974215893808968,0.6407806873321533,0.8445428725721186,0.5908264739709724
|
||||
B5_mofe_mlp,3407,0.3/synchrony_async,0.16594815654028122,728,0.6387362637362637,0.6044534328871108,0.6384277939796448,0.8368071907382745,0.6014610241367565
|
||||
B5_mofe_mlp,2026,0.0/none,0.0,728,0.6318681318681318,0.596526187825028,0.6597292423248291,0.8489002293710785,0.6032696127085834
|
||||
B5_mofe_mlp,2026,0.1/single,0.03371342897433643,728,0.6332417582417582,0.5970636969424238,0.6549333333969116,0.84639998483126,0.6035253872373745
|
||||
B5_mofe_mlp,2026,0.1/sync,0.045156406674301666,728,0.6277472527472527,0.5913100989187946,0.6568704843521118,0.8449213938859407,0.603907181971587
|
||||
B5_mofe_mlp,2026,0.1/partial,0.040239075593981495,728,0.6401098901098901,0.6024246836534827,0.6604945659637451,0.8481462530229538,0.6010193432821422
|
||||
B5_mofe_mlp,2026,0.1/async,0.042147033495012594,728,0.6332417582417582,0.5970167867969366,0.6555314660072327,0.8447819862485282,0.6044813102528398
|
||||
B5_mofe_mlp,2026,0.3/single,0.10101503353205936,728,0.6112637362637363,0.5638798050124324,0.6562340259552002,0.8475582224333787,0.5979011819911703
|
||||
B5_mofe_mlp,2026,0.3/sync,0.15049590345982738,728,0.6373626373626373,0.5989757153812737,0.6513807773590088,0.8493299353562517,0.595392891922453
|
||||
B5_mofe_mlp,2026,0.3/partial,0.11254067775371336,728,0.6181318681318682,0.5709193418039654,0.6664141416549683,0.8523418464954076,0.5914931558714205
|
||||
B5_mofe_mlp,2026,0.3/async,0.1402331971734938,728,0.6291208791208791,0.5870988936388463,0.6590703129768372,0.8508121089050296,0.5900941328826028
|
||||
B5_mofe_mlp,2026,0.5/single,0.16749406682715026,728,0.6126373626373627,0.5657169221458677,0.667115330696106,0.8635330523409043,0.5791727571395311
|
||||
B5_mofe_mlp,2026,0.5/sync,0.2869043063014706,728,0.6291208791208791,0.5857551126223407,0.6644048094749451,0.8677120855890653,0.5713612415242764
|
||||
B5_mofe_mlp,2026,0.5/partial,0.19417960020144912,728,0.6071428571428571,0.5531815016401854,0.6734310984611511,0.8739539092129627,0.5636138803720933
|
||||
B5_mofe_mlp,2026,0.5/async,0.2674778555592227,728,0.6002747252747253,0.5462966876593826,0.6667307019233704,0.8750358982896606,0.5594822701935701
|
||||
B5_mofe_mlp,2026,0.7/single,0.233161167473855,728,0.6057692307692307,0.5505603733738087,0.6735425591468811,0.8787421518357899,0.5616953487570775
|
||||
B5_mofe_mlp,2026,0.7/sync,0.4688425032750801,728,0.6332417582417582,0.5849499933341841,0.6716032028198242,0.874264169285277,0.5570492921944442
|
||||
B5_mofe_mlp,2026,0.7/partial,0.3517369377138981,728,0.6043956043956044,0.5413011359929573,0.6734654903411865,0.8867611643860307,0.5492658387339109
|
||||
B5_mofe_mlp,2026,0.7/async,0.43688540417216304,728,0.5824175824175825,0.5164414243555493,0.6856517791748047,0.9007994081729855,0.5242932038005764
|
||||
B5_mofe_mlp,2026,0.3/modality_T,0.05864506749840218,728,0.6291208791208791,0.5851588544385288,0.6609874367713928,0.8549948646993513,0.586805018488965
|
||||
B5_mofe_mlp,2026,0.3/modality_A,0.05697909847839254,728,0.6263736263736264,0.5923935684031888,0.6586064100265503,0.8480335925101825,0.60334875155725
|
||||
B5_mofe_mlp,2026,0.3/modality_V,0.05703409792921816,728,0.6277472527472527,0.5893350885736607,0.665980339050293,0.8524798430579631,0.6000276703946874
|
||||
B5_mofe_mlp,2026,0.3/modality_TA,0.10919187418833474,728,0.6318681318681318,0.587396209053305,0.6626462936401367,0.8586239046697091,0.5775735874993875
|
||||
B5_mofe_mlp,2026,0.3/modality_TV,0.11437644408481795,728,0.6222527472527473,0.5738086078934214,0.6704530119895935,0.866302760610593,0.5774709040224134
|
||||
B5_mofe_mlp,2026,0.3/modality_AV,0.11303721690563862,728,0.625,0.5916277684292892,0.6536700129508972,0.8439307195897752,0.6074596191049758
|
||||
B5_mofe_mlp,2026,0.3/modality_TAV,0.16956369042443203,728,0.6208791208791209,0.5812583811618302,0.6594159007072449,0.849905694610642,0.5970091338142024
|
||||
B5_mofe_mlp,2026,0.3/location_start_T,0.10048832030833439,728,0.6153846153846154,0.5618821946453657,0.6588675379753113,0.8592022115222522,0.5808518864395622
|
||||
B5_mofe_mlp,2026,0.3/location_middle_T,0.10048832030833439,728,0.635989010989011,0.5824702411988757,0.6568567156791687,0.8484010017651692,0.5967801637287061
|
||||
B5_mofe_mlp,2026,0.3/location_end_T,0.10048832030833439,728,0.625,0.5698652866175331,0.6648644208908081,0.8535741441162473,0.5882863910037036
|
||||
B5_mofe_mlp,2026,0.3/span_long_T,0.10048832030833439,728,0.6236263736263736,0.562985436305976,0.6574857831001282,0.8555561177828485,0.5918958078441902
|
||||
B5_mofe_mlp,2026,0.3/span_multi_short_T,0.10048832030833439,728,0.6277472527472527,0.5726133028329055,0.6584722995758057,0.8555951308170282,0.5927028642691361
|
||||
B5_mofe_mlp,2026,0.3/location_start_A,0.10087109490306286,728,0.6318681318681318,0.5946901594150785,0.6520330905914307,0.8433031735725448,0.6073570509720814
|
||||
B5_mofe_mlp,2026,0.3/location_middle_A,0.10087109490306286,728,0.6318681318681318,0.5964427935908233,0.6560055017471313,0.8459685792205899,0.6055766417612172
|
||||
B5_mofe_mlp,2026,0.3/location_end_A,0.10087109490306286,728,0.6304945054945055,0.5954019090935031,0.6567164659500122,0.8454491143527618,0.606308967978668
|
||||
B5_mofe_mlp,2026,0.3/span_long_A,0.10087109490306286,728,0.6346153846153846,0.5984529560616517,0.6542528867721558,0.8456221050542772,0.6045499685036667
|
||||
B5_mofe_mlp,2026,0.3/span_multi_short_A,0.10087109490306286,728,0.6291208791208791,0.5940461219915539,0.652047872543335,0.8438097261553195,0.6066816421615474
|
||||
B5_mofe_mlp,2026,0.3/location_start_V,0.09701596125937247,728,0.625,0.5846195652173912,0.6589953899383545,0.8472817644100747,0.6052728090813515
|
||||
B5_mofe_mlp,2026,0.3/location_middle_V,0.09701596125937247,728,0.6332417582417582,0.5924845794271737,0.6621479392051697,0.8497565832531178,0.604477594980146
|
||||
B5_mofe_mlp,2026,0.3/location_end_V,0.09701596125937247,728,0.635989010989011,0.5966448674232786,0.6628890633583069,0.8499398476690037,0.6041605414076311
|
||||
B5_mofe_mlp,2026,0.3/span_long_V,0.09701596125937247,728,0.6318681318681318,0.5920418130355286,0.6612062454223633,0.8490313438115848,0.6043638943646987
|
||||
B5_mofe_mlp,2026,0.3/span_multi_short_V,0.09701596125937247,728,0.6304945054945055,0.5901013226297688,0.6599566340446472,0.8482730221309799,0.6053465874208716
|
||||
B5_mofe_mlp,2026,0.3/synchrony_sync,0.17627119309968198,728,0.6332417582417582,0.5960026820501673,0.661083996295929,0.85475512137696,0.5907962734135933
|
||||
B5_mofe_mlp,2026,0.3/synchrony_partial,0.11943882005826376,728,0.625,0.5813376007663962,0.6566504836082458,0.8541285149652549,0.5872303717344893
|
||||
B5_mofe_mlp,2026,0.3/synchrony_async,0.16594815654028122,728,0.6346153846153846,0.5921399047232352,0.6548778414726257,0.8516002961616485,0.5907794067608744
|
||||
|
+7
@@ -0,0 +1,7 @@
|
||||
method,seed,n_test,accuracy,macro_f1,mae,rmse,pearson
|
||||
B0_early_concat,42,727,0.6740027510316369,0.5899364073506269,0.6732717752456665,0.8909249051748226,0.650797420132884
|
||||
B0_early_concat,3407,727,0.6616231086657497,0.5828956102942167,0.6562737822532654,0.8698196330495139,0.6629223076526239
|
||||
B0_early_concat,2026,727,0.671251719394773,0.5855120860972955,0.6805484890937805,0.8901024339427269,0.6502357150725873
|
||||
B5_mofe_mlp,42,727,0.6588720770288858,0.5881517532839975,0.6833341121673584,0.8967927556093251,0.6416499042677164
|
||||
B5_mofe_mlp,3407,727,0.6629986244841816,0.5987075270336911,0.6780627965927124,0.8830488445601224,0.6511876181785311
|
||||
B5_mofe_mlp,2026,727,0.6740027510316369,0.6049338687002567,0.6956164836883545,0.9003428945074896,0.6396089629278374
|
||||
|
+6
@@ -0,0 +1,6 @@
|
||||
comparison,metric,delta_mean_over_seeds,bootstrap_ci_2p5,bootstrap_ci_97p5,bootstrap_probability_delta_gt_0,replicates,resampling_unit,paired,seed
|
||||
MoFE-7 + MLP Router minus EarlyConcat + BiGRU,accuracy,-0.003668042182485065,-0.017722402708141464,0.011162107799884273,0.295,1000,source video id,True,20260925
|
||||
MoFE-7 + MLP Router minus EarlyConcat + BiGRU,macro_f1,0.011149681758602092,-0.008115389318624997,0.03215508906599282,0.888,1000,source video id,True,20260925
|
||||
MoFE-7 + MLP Router minus EarlyConcat + BiGRU,mae,0.015639781951904297,0.0053533881902694345,0.027328948676586112,0.998,1000,source video id,True,20260925
|
||||
MoFE-7 + MLP Router minus EarlyConcat + BiGRU,rmse,0.009779174169957994,-0.001325107979073983,0.021876485489001028,0.954,1000,source video id,True,20260925
|
||||
MoFE-7 + MLP Router minus EarlyConcat + BiGRU,pearson,-0.010502985828003353,-0.0207993259194662,-0.0015367106204170408,0.015,1000,source video id,True,20260925
|
||||
|
+11
@@ -0,0 +1,11 @@
|
||||
method,metric,mean,sd_across_seeds
|
||||
B0_early_concat,accuracy,0.6689591930307198,0.006500434148903153
|
||||
B0_early_concat,macro_f1,0.5861147012473796,0.0035588712482642632
|
||||
B0_early_concat,mae,0.6700313488642374,0.01245755274515561
|
||||
B0_early_concat,rmse,0.8836156573890211,0.011954782742238058
|
||||
B0_early_concat,pearson,0.6546518142860317,0.007167961602772788
|
||||
B5_mofe_mlp,accuracy,0.6652911508482348,0.007821514034494262
|
||||
B5_mofe_mlp,macro_f1,0.5972643830059817,0.00848362233805206
|
||||
B5_mofe_mlp,mae,0.6856711308161417,0.009007176293739278
|
||||
B5_mofe_mlp,rmse,0.8933948315589791,0.009134027413164894
|
||||
B5_mofe_mlp,pearson,0.6441488284580283,0.006180597134201404
|
||||
|
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"experiment": "Frozen EarlyConcat vs MoFE-7 evaluation under math/Q2 test protocol",
|
||||
"created_unix": 1790283893.6609955,
|
||||
"device": "cuda",
|
||||
"cuda_device": "NVIDIA GeForce RTX 5070 Ti",
|
||||
"feature_file": "/home/gloamxun/modeling_zhaocui/E\u9898\u6570\u636e/\u9644\u4ef62-\u6570\u636e\u96c6\u7279\u5f81\u6587\u4ef6/aligned_50.pkl",
|
||||
"feature_sha256": "66e867aa74bc70a844e806e5571e371c9abb4a35f9e2887ce9b4d97ff2cb8fcd",
|
||||
"representation": "official aligned_50 ordered positions; not physical-time bins",
|
||||
"train_valid_test_counts": {
|
||||
"train": 3395,
|
||||
"valid": 728,
|
||||
"test": 727
|
||||
},
|
||||
"source_video_groups": {
|
||||
"train": 1528,
|
||||
"valid": 239,
|
||||
"test": 381
|
||||
},
|
||||
"official_group_splits_disjoint": true,
|
||||
"test_evaluation": "test outputs preserved from the earlier single evaluation; no test prediction was rerun",
|
||||
"test_prediction_performed_this_invocation": false,
|
||||
"seeds": [
|
||||
42,
|
||||
3407,
|
||||
2026
|
||||
],
|
||||
"checkpoint_source": "/home/gloamxun/modeling_zhaocui/deep_learning/Q2/outputs/followups/R01_selected_model_reevaluation/models",
|
||||
"train_only_scaler": "/home/gloamxun/modeling_zhaocui/deep_learning/Q2/outputs/followups/R01_selected_model_reevaluation/aligned_robust_stats.npz",
|
||||
"scaler_max_abs_difference_from_train_refit": 0.0,
|
||||
"test_labels_used_for_training_or_selection": false,
|
||||
"controlled_missingness": {
|
||||
"scenario_seed": 20261833,
|
||||
"scenario_design": "math/Q2 42-scenario design regenerated on the Q2 models' BERT attention-mask base",
|
||||
"scenarios": 42,
|
||||
"AURC": "normalized trapezoidal area of MAE over realized equal-modality-weighted added missing rate, at 0/.1/.3/.5/.7 for single/sync/partial/async"
|
||||
},
|
||||
"bootstrap": {
|
||||
"replicates": 1000,
|
||||
"test_seed": 20260925,
|
||||
"aurc_seed": 20260926,
|
||||
"unit": "source video id",
|
||||
"paired": true
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,73 @@
|
||||
# Q2 retraining under the math/Q2 V2 evaluation protocol
|
||||
|
||||
## Protocol
|
||||
|
||||
- Official Attachment 2 split: 3,395 train / 728 validation / 727 test samples; source-video groups are disjoint.
|
||||
- Seed: `20260924`, matching the math/Q2 run.
|
||||
- Both models were retrained from scratch with the same train-only median/MAD scaler, training masks, batch order, optimizer, and joint objective.
|
||||
- Training masks use contiguous spans at rates 0%, 10%, 30%, 50%, and 70%, with `single`, `sync`, `partial`, or `async` patterns. At least 20% of originally observed positions are retained in each selected modality.
|
||||
- AdamW: learning rate `3e-4`, weight decay `1e-3`, batch size 64, maximum 12 epochs, early-stopping patience 3.
|
||||
- Checkpoint selection uses the mean validation `CE + 0.5 × SmoothL1` over `0.0/none`, `0.3/single`, `0.3/sync`, and `0.5/async`. Both models selected epoch 3.
|
||||
- The official test set was evaluated once, after checkpoint selection, on its clean observation masks. No test label was used for fitting or selection.
|
||||
- The 42 controlled missingness scenarios and AURC-MAE were evaluated on validation data. Confidence intervals use 1,000 paired bootstrap resamples of source-video groups.
|
||||
|
||||
The existing deterministic model heads and joint CE + SmoothL1 objective were retained. The math/Q2 C5 probabilistic Beta-mixture loss cannot be applied to these two architectures without changing the models. Thus the split, missingness, checkpoint discipline, and test metrics follow the math/Q2 protocol, while the training objective is the existing Q2 objective.
|
||||
|
||||
## Official test results
|
||||
|
||||
| Model | Accuracy ↑ | Macro-F1 ↑ | MAE ↓ | RMSE ↓ | Pearson ↑ |
|
||||
|---|---:|---:|---:|---:|---:|
|
||||
| EarlyConcat + BiGRU | 0.6740 | **0.6157** | **0.6624** | **0.8897** | **0.6585** |
|
||||
| MoFE-7 + MLP Router | **0.6795** | 0.6049 | 0.6761 | 0.8980 | 0.6427 |
|
||||
|
||||
Paired bootstrap differences are `MoFE-7 − EarlyConcat`; all 95% intervals include zero.
|
||||
|
||||
| Metric | Difference | 95% source-video bootstrap interval |
|
||||
|---|---:|---:|
|
||||
| Accuracy | +0.0055 | [-0.0259, +0.0339] |
|
||||
| Macro-F1 | -0.0109 | [-0.0475, +0.0216] |
|
||||
| MAE | +0.0137 | [-0.0065, +0.0353] |
|
||||
| RMSE | +0.0083 | [-0.0150, +0.0327] |
|
||||
| Pearson | -0.0159 | [-0.0323, +0.0013] |
|
||||
|
||||
The point estimates favor EarlyConcat on Macro-F1 and regression metrics; MoFE-7 has slightly higher Accuracy. The group-bootstrap intervals do not establish a clear difference on this single-seed run.
|
||||
|
||||
## Validation missingness results
|
||||
|
||||
Unweighted averages over the 41 non-clean rows of the 42-scenario audit are supplementary summaries; they are not the AURC statistic.
|
||||
|
||||
| Model | Clean Macro-F1 | Mean Macro-F1 over 41 masked scenarios | Worst masked scenario Macro-F1 | Mean MAE over 41 masked scenarios |
|
||||
|---|---:|---:|---:|---:|
|
||||
| EarlyConcat + BiGRU | **0.5746** | **0.5655** | **0.5289** (`0.3/location_start_T`) | **0.6371** |
|
||||
| MoFE-7 + MLP Router | 0.5626 | 0.5513 | 0.5048 (`0.7/partial`) | 0.6453 |
|
||||
|
||||
| 42-scenario AURC-MAE mode | EarlyConcat | MoFE-7 | MoFE-7 − EarlyConcat (95% group-bootstrap interval) |
|
||||
|---|---:|---:|---:|
|
||||
| Single | **0.6379** | 0.6494 | +0.0115 [-0.0082, +0.0302] |
|
||||
| Sync | **0.6387** | 0.6461 | +0.0074 [-0.0120, +0.0250] |
|
||||
| Partial | **0.6420** | 0.6527 | +0.0107 [-0.0087, +0.0285] |
|
||||
| Async | **0.6409** | 0.6527 | +0.0119 [-0.0062, +0.0289] |
|
||||
|
||||
Lower AURC-MAE is better. EarlyConcat has the lower point estimate in all four modes; each interval crosses zero.
|
||||
|
||||
At 30% modality-specific missingness:
|
||||
|
||||
| Scenario | EarlyConcat Macro-F1 / MAE | MoFE-7 Macro-F1 / MAE |
|
||||
|---|---:|---:|
|
||||
| Text only | 0.5462 / 0.6386 | 0.5455 / 0.6477 |
|
||||
| Audio + Vision | 0.5817 / 0.6326 | 0.5620 / 0.6350 |
|
||||
| All modalities | 0.5693 / 0.6352 | 0.5617 / 0.6421 |
|
||||
|
||||
## Reading the result
|
||||
|
||||
Under this retraining run, EarlyConcat is the stronger overall choice by Macro-F1, MAE, Pearson, mean masked-scenario metrics, and all four AURC-MAE point estimates. MoFE-7's small Accuracy advantage is uncertain. Because this is one seed, the results should be read as a protocol-matched run rather than a multi-seed stability estimate.
|
||||
|
||||
The math/Q2 report's C5 test result (Accuracy 0.6740, Macro-F1 0.5861, MAE 0.6980, RMSE 0.9674, Pearson 0.6300) is included only as context: C5 has a different probabilistic output head and loss, so it is not a like-for-like architecture comparison.
|
||||
|
||||
## Artifacts
|
||||
|
||||
- `run_manifest.json`: data, split, training, validation, test, and bootstrap protocol.
|
||||
- `official_test_metrics_by_seed.csv`, `official_test_paired_bootstrap.csv`: final test metrics and paired group intervals.
|
||||
- `controlled_metrics_by_scenario.csv`, `aurc_mae_by_mode_seed.csv`, `aurc_mae_paired_bootstrap.csv`: controlled validation evaluation.
|
||||
- `training_history.csv`, `training_mask_distribution.csv`, `parameter_count.csv`: training diagnostics.
|
||||
- `models/`: selected checkpoints and per-model histories.
|
||||
BIN
Binary file not shown.
+9
@@ -0,0 +1,9 @@
|
||||
method,seed,mask_mode,aurc_mae,rates_realized
|
||||
B0_early_concat,20260924,single,0.6378559862834174,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B0_early_concat,20260924,sync,0.6387340663515244,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B0_early_concat,20260924,partial,0.6419565330457959,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B0_early_concat,20260924,async,0.6408780951419853,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
B5_mofe_mlp,20260924,single,0.6493678370419695,"[0.0, 0.03371342897433643, 0.10101503353205936, 0.16749406682715026, 0.233161167473855]"
|
||||
B5_mofe_mlp,20260924,sync,0.6461235184522032,"[0.0, 0.045156406674301666, 0.15049590345982738, 0.2869043063014706, 0.4688425032750801]"
|
||||
B5_mofe_mlp,20260924,partial,0.6526607283449438,"[0.0, 0.040239075593981495, 0.11254067775371336, 0.19417960020144912, 0.3517369377138981]"
|
||||
B5_mofe_mlp,20260924,async,0.6527283697618514,"[0.0, 0.042147033495012594, 0.1402331971734938, 0.2674778555592227, 0.43688540417216304]"
|
||||
|
+5
@@ -0,0 +1,5 @@
|
||||
mask_mode,delta_aurc_mae_mofe_minus_earlyconcat,bootstrap_ci_2p5,bootstrap_ci_97p5,bootstrap_probability_delta_lt_0,replicates,resampling_unit,paired,seed
|
||||
single,0.0115118507585521,-0.008162294605830693,0.0301810704036703,0.147,1000,source video id,True,20260926
|
||||
sync,0.007389452100678762,-0.011956058947051679,0.024951573659996493,0.259,1000,source video id,True,20260926
|
||||
partial,0.0107041952991479,-0.008660331894343192,0.028507998549019406,0.161,1000,source video id,True,20260926
|
||||
async,0.011850274619866097,-0.006150395373279235,0.028900548840914045,0.115,1000,source video id,True,20260926
|
||||
|
+85
@@ -0,0 +1,85 @@
|
||||
method,seed,scenario,realized_additional_global_rate,n_valid,accuracy,macro_f1,mae,rmse,pearson
|
||||
B0_early_concat,20260924,0.0/none,0.0,728,0.6153846153846154,0.5746473167631652,0.6343159675598145,0.8547929855610467,0.6094602929761117
|
||||
B0_early_concat,20260924,0.1/single,0.03371342897433643,728,0.6085164835164835,0.5664719454034405,0.6328904032707214,0.85180821504718,0.6094495047174566
|
||||
B0_early_concat,20260924,0.1/sync,0.045156406674301666,728,0.6098901098901099,0.572216012695813,0.6333207488059998,0.8524984763011572,0.6076810890989575
|
||||
B0_early_concat,20260924,0.1/partial,0.040239075593981495,728,0.6112637362637363,0.5706507860891473,0.6365461945533752,0.8541368192404588,0.6058859344866191
|
||||
B0_early_concat,20260924,0.1/async,0.042147033495012594,728,0.6181318681318682,0.57972935597245,0.6354024410247803,0.852031893370522,0.6096049530317527
|
||||
B0_early_concat,20260924,0.3/single,0.10101503353205936,728,0.614010989010989,0.574220027013609,0.6334993839263916,0.854360969277559,0.6003605729983688
|
||||
B0_early_concat,20260924,0.3/sync,0.15049590345982738,728,0.6167582417582418,0.5730892523600383,0.630831241607666,0.8516494286640907,0.6037950917057342
|
||||
B0_early_concat,20260924,0.3/partial,0.11254067775371336,728,0.5961538461538461,0.5524892450018223,0.6370627880096436,0.8509616306790629,0.5979238186423941
|
||||
B0_early_concat,20260924,0.3/async,0.1402331971734938,728,0.6112637362637363,0.5642957517004324,0.6346827745437622,0.8484940848967643,0.6016212338363784
|
||||
B0_early_concat,20260924,0.5/single,0.16749406682715026,728,0.6085164835164835,0.5670184055357302,0.641832172870636,0.8632332628816644,0.584865558206941
|
||||
B0_early_concat,20260924,0.5/sync,0.2869043063014706,728,0.6167582417582418,0.5778898483774816,0.6371996998786926,0.8516882007461904,0.5924273843364904
|
||||
B0_early_concat,20260924,0.5/partial,0.19417960020144912,728,0.6043956043956044,0.5555283579204368,0.6441753506660461,0.8556262354706008,0.58203768440478
|
||||
B0_early_concat,20260924,0.5/async,0.2674778555592227,728,0.6016483516483516,0.5562522166489335,0.6466042995452881,0.8691973721270065,0.5700682850933873
|
||||
B0_early_concat,20260924,0.7/single,0.233161167473855,728,0.5947802197802198,0.5485981680163076,0.6481859087944031,0.8809218965997698,0.5635469635745481
|
||||
B0_early_concat,20260924,0.7/sync,0.4688425032750801,728,0.5989010989010989,0.5626788755858914,0.6574939489364624,0.8839283533082283,0.5530534634060382
|
||||
B0_early_concat,20260924,0.7/partial,0.3517369377138981,728,0.5865384615384616,0.5362416499854459,0.649185299873352,0.8699182696154274,0.5583734809756835
|
||||
B0_early_concat,20260924,0.7/async,0.43688540417216304,728,0.5906593406593407,0.5452478413289441,0.6452565789222717,0.8735732640099089,0.5557409742879581
|
||||
B0_early_concat,20260924,0.3/modality_T,0.05864506749840218,728,0.5934065934065934,0.5462207369967149,0.6385592818260193,0.8588612841667281,0.5881575690894479
|
||||
B0_early_concat,20260924,0.3/modality_A,0.05697909847839254,728,0.6195054945054945,0.5811293545443177,0.6334327459335327,0.8554246446919079,0.6094268235049153
|
||||
B0_early_concat,20260924,0.3/modality_V,0.05703409792921816,728,0.6085164835164835,0.5686488097327915,0.6339969038963318,0.8540853174750868,0.6090671394991262
|
||||
B0_early_concat,20260924,0.3/modality_TA,0.10919187418833474,728,0.6071428571428571,0.5602184289914843,0.6519798636436462,0.8699653056231473,0.5768200282380198
|
||||
B0_early_concat,20260924,0.3/modality_TV,0.11437644408481795,728,0.6016483516483516,0.5551175139246832,0.6393751502037048,0.8553959366977271,0.586114371400815
|
||||
B0_early_concat,20260924,0.3/modality_AV,0.11303721690563862,728,0.6181318681318682,0.5816591704230339,0.6326149702072144,0.849950156433407,0.6139148157800808
|
||||
B0_early_concat,20260924,0.3/modality_TAV,0.16956369042443203,728,0.6098901098901099,0.5693316484741863,0.635162353515625,0.8552724883114987,0.603834533975782
|
||||
B0_early_concat,20260924,0.3/location_start_T,0.10048832030833439,728,0.592032967032967,0.5289423490769057,0.6485703587532043,0.8620428808968518,0.58162843015804
|
||||
B0_early_concat,20260924,0.3/location_middle_T,0.10048832030833439,728,0.603021978021978,0.5536695658136993,0.6376606822013855,0.8514152889573482,0.5897726128244986
|
||||
B0_early_concat,20260924,0.3/location_end_T,0.10048832030833439,728,0.6043956043956044,0.5556056212627483,0.6402567625045776,0.8542722582486372,0.5891006734385348
|
||||
B0_early_concat,20260924,0.3/span_long_T,0.10048832030833439,728,0.5989010989010989,0.5420906602882528,0.6381194591522217,0.8522570166440261,0.5853301068267182
|
||||
B0_early_concat,20260924,0.3/span_multi_short_T,0.10048832030833439,728,0.5975274725274725,0.5440495562446782,0.6356171369552612,0.8507890951392163,0.5876002847201148
|
||||
B0_early_concat,20260924,0.3/location_start_A,0.10087109490306286,728,0.6167582417582418,0.5812912542814239,0.6293162107467651,0.8535272872442308,0.6114908900853474
|
||||
B0_early_concat,20260924,0.3/location_middle_A,0.10087109490306286,728,0.625,0.5898724710749466,0.6324224472045898,0.8539363426497163,0.6110184042952445
|
||||
B0_early_concat,20260924,0.3/location_end_A,0.10087109490306286,728,0.6263736263736264,0.5905371029206817,0.6318912506103516,0.8519847767795174,0.6123387287503104
|
||||
B0_early_concat,20260924,0.3/span_long_A,0.10087109490306286,728,0.6181318681318682,0.583726857007959,0.6294587254524231,0.8517886220306001,0.6128556406770401
|
||||
B0_early_concat,20260924,0.3/span_multi_short_A,0.10087109490306286,728,0.6126373626373627,0.5775040835891835,0.6295161247253418,0.8519002262223094,0.6129813734377794
|
||||
B0_early_concat,20260924,0.3/location_start_V,0.09701596125937247,728,0.6167582417582418,0.5784311415271869,0.6317656636238098,0.8524039774314564,0.6094092868851544
|
||||
B0_early_concat,20260924,0.3/location_middle_V,0.09701596125937247,728,0.6126373626373627,0.5758902475296572,0.6318002343177795,0.8514377607625061,0.6102280937754011
|
||||
B0_early_concat,20260924,0.3/location_end_V,0.09701596125937247,728,0.6085164835164835,0.5710858841987924,0.6308775544166565,0.8521441651682452,0.6096283880242306
|
||||
B0_early_concat,20260924,0.3/span_long_V,0.09701596125937247,728,0.6098901098901099,0.5712207484964352,0.6293761730194092,0.8494720698811937,0.6119813338293026
|
||||
B0_early_concat,20260924,0.3/span_multi_short_V,0.09701596125937247,728,0.6112637362637363,0.5724471470092743,0.6319549083709717,0.8523396436835378,0.609626822827826
|
||||
B0_early_concat,20260924,0.3/synchrony_sync,0.17627119309968198,728,0.6071428571428571,0.5695955472926512,0.6377636194229126,0.8563529196373093,0.6014507911006194
|
||||
B0_early_concat,20260924,0.3/synchrony_partial,0.11943882005826376,728,0.614010989010989,0.5684426287766249,0.637352466583252,0.8497644743263203,0.5966725971941069
|
||||
B0_early_concat,20260924,0.3/synchrony_async,0.16594815654028122,728,0.6126373626373627,0.5674224398503759,0.6281272768974304,0.8457619380102747,0.6032017513238488
|
||||
B5_mofe_mlp,20260924,0.0/none,0.0,728,0.6057692307692307,0.5626447626447627,0.6368198394775391,0.8559372894743668,0.6043374371906683
|
||||
B5_mofe_mlp,20260924,0.1/single,0.03371342897433643,728,0.603021978021978,0.5577024380655372,0.6354461312294006,0.8543030622177138,0.6043309492398073
|
||||
B5_mofe_mlp,20260924,0.1/sync,0.045156406674301666,728,0.6016483516483516,0.5578604237235317,0.6360094547271729,0.8566200486967864,0.6013163340141866
|
||||
B5_mofe_mlp,20260924,0.1/partial,0.040239075593981495,728,0.6043956043956044,0.5556321720066021,0.6396713852882385,0.8584938039739364,0.6010106097514567
|
||||
B5_mofe_mlp,20260924,0.1/async,0.042147033495012594,728,0.6016483516483516,0.5565284878755451,0.6399586200714111,0.8586023845707027,0.6003751700281593
|
||||
B5_mofe_mlp,20260924,0.3/single,0.10101503353205936,728,0.6016483516483516,0.541701381711408,0.6420438289642334,0.8560677438828654,0.6001244469401612
|
||||
B5_mofe_mlp,20260924,0.3/sync,0.15049590345982738,728,0.614010989010989,0.5693500431359637,0.6388541460037231,0.855140553404774,0.6004973824912962
|
||||
B5_mofe_mlp,20260924,0.3/partial,0.11254067775371336,728,0.6002747252747253,0.539363851343671,0.6399300694465637,0.852451385499069,0.600576671641639
|
||||
B5_mofe_mlp,20260924,0.3/async,0.1402331971734938,728,0.6112637362637363,0.5574919295976676,0.6433636546134949,0.8590869073880102,0.5949047660811583
|
||||
B5_mofe_mlp,20260924,0.5/single,0.16749406682715026,728,0.6153846153846154,0.5586891334012748,0.6575657725334167,0.8704040602456963,0.5845020723393936
|
||||
B5_mofe_mlp,20260924,0.5/sync,0.2869043063014706,728,0.6236263736263736,0.5743149665205417,0.6494404673576355,0.861759830163145,0.5863964302751469
|
||||
B5_mofe_mlp,20260924,0.5/partial,0.19417960020144912,728,0.6071428571428571,0.5355878409861167,0.6588982939720154,0.8727261767123125,0.5771476109647259
|
||||
B5_mofe_mlp,20260924,0.5/async,0.2674778555592227,728,0.6071428571428571,0.5480764166366612,0.6661632657051086,0.8843453864002215,0.5607269390754831
|
||||
B5_mofe_mlp,20260924,0.7/single,0.233161167473855,728,0.5975274725274725,0.5338090526934354,0.6756492257118225,0.8963052076097996,0.5586007231842708
|
||||
B5_mofe_mlp,20260924,0.7/sync,0.4688425032750801,728,0.6085164835164835,0.565745648642757,0.6606540679931641,0.8915316333902972,0.5541614851997242
|
||||
B5_mofe_mlp,20260924,0.7/partial,0.3517369377138981,728,0.5879120879120879,0.5047590693139797,0.6689532995223999,0.8808325448358977,0.5652797535160367
|
||||
B5_mofe_mlp,20260924,0.7/async,0.43688540417216304,728,0.592032967032967,0.5358739987222959,0.6561869382858276,0.8794836563621672,0.5588249328667847
|
||||
B5_mofe_mlp,20260924,0.3/modality_T,0.05864506749840218,728,0.6057692307692307,0.5454628701133298,0.6476889252662659,0.8713019083833805,0.5849661557179732
|
||||
B5_mofe_mlp,20260924,0.3/modality_A,0.05697909847839254,728,0.6098901098901099,0.5668229481750353,0.6372511386871338,0.8576914509064657,0.6038199443939388
|
||||
B5_mofe_mlp,20260924,0.3/modality_V,0.05703409792921816,728,0.6085164835164835,0.5658571865320935,0.635873556137085,0.8509052084722697,0.6033888741448421
|
||||
B5_mofe_mlp,20260924,0.3/modality_TA,0.10919187418833474,728,0.6085164835164835,0.551328601397119,0.6482953429222107,0.8684097474486374,0.5835353299125547
|
||||
B5_mofe_mlp,20260924,0.3/modality_TV,0.11437644408481795,728,0.6098901098901099,0.5553867994131184,0.6396345496177673,0.8586720452609139,0.587121236120106
|
||||
B5_mofe_mlp,20260924,0.3/modality_AV,0.11303721690563862,728,0.603021978021978,0.5619825935453588,0.6350018382072449,0.8494499320015197,0.60596049079492
|
||||
B5_mofe_mlp,20260924,0.3/modality_TAV,0.16956369042443203,728,0.6043956043956044,0.5616850220473674,0.6421029567718506,0.8664177923921365,0.5936093549207478
|
||||
B5_mofe_mlp,20260924,0.3/location_start_T,0.10048832030833439,728,0.5824175824175825,0.5074646922437304,0.6651872396469116,0.8883185050888599,0.5708209590446683
|
||||
B5_mofe_mlp,20260924,0.3/location_middle_T,0.10048832030833439,728,0.6071428571428571,0.5255359991732577,0.6560966968536377,0.8699031271111219,0.5868176227041925
|
||||
B5_mofe_mlp,20260924,0.3/location_end_T,0.10048832030833439,728,0.6071428571428571,0.5241847210214233,0.6566184759140015,0.8703728673739797,0.5880970537326943
|
||||
B5_mofe_mlp,20260924,0.3/span_long_T,0.10048832030833439,728,0.592032967032967,0.5179866041214112,0.6569079756736755,0.8722153699980981,0.5832300823948291
|
||||
B5_mofe_mlp,20260924,0.3/span_multi_short_T,0.10048832030833439,728,0.5975274725274725,0.5217755256072807,0.6542142033576965,0.8695648872333397,0.5861358594281869
|
||||
B5_mofe_mlp,20260924,0.3/location_start_A,0.10087109490306286,728,0.6153846153846154,0.5693105809612327,0.6393567323684692,0.8605473930921826,0.6030681972111498
|
||||
B5_mofe_mlp,20260924,0.3/location_middle_A,0.10087109490306286,728,0.6002747252747253,0.551121695858538,0.6374183297157288,0.8570439020438321,0.6040473734185878
|
||||
B5_mofe_mlp,20260924,0.3/location_end_A,0.10087109490306286,728,0.6043956043956044,0.5553975345642012,0.6361827850341797,0.8545916515771931,0.6057378355308779
|
||||
B5_mofe_mlp,20260924,0.3/span_long_A,0.10087109490306286,728,0.6071428571428571,0.5568552904967875,0.6383994817733765,0.8585218529627641,0.603334225974666
|
||||
B5_mofe_mlp,20260924,0.3/span_multi_short_A,0.10087109490306286,728,0.6085164835164835,0.5639201931530282,0.6405740976333618,0.8599686392899067,0.6018797003793258
|
||||
B5_mofe_mlp,20260924,0.3/location_start_V,0.09701596125937247,728,0.614010989010989,0.5706553787814322,0.6286044120788574,0.843568535117206,0.607697827670399
|
||||
B5_mofe_mlp,20260924,0.3/location_middle_V,0.09701596125937247,728,0.6057692307692307,0.5625629140502925,0.631475567817688,0.8447082164734656,0.6066031598751728
|
||||
B5_mofe_mlp,20260924,0.3/location_end_V,0.09701596125937247,728,0.6016483516483516,0.5591251566861323,0.6326090097427368,0.8460766185600626,0.6050984837070122
|
||||
B5_mofe_mlp,20260924,0.3/span_long_V,0.09701596125937247,728,0.6153846153846154,0.5732705025992542,0.629095733165741,0.8440032861383474,0.6077357791248426
|
||||
B5_mofe_mlp,20260924,0.3/span_multi_short_V,0.09701596125937247,728,0.6098901098901099,0.5658045462820314,0.6311919093132019,0.8445015138936631,0.6068331137272684
|
||||
B5_mofe_mlp,20260924,0.3/synchrony_sync,0.17627119309968198,728,0.6085164835164835,0.5675933141063153,0.6438319683074951,0.8657874068623187,0.5957094024638004
|
||||
B5_mofe_mlp,20260924,0.3/synchrony_partial,0.11943882005826376,728,0.6057692307692307,0.542036764873725,0.6417625546455383,0.8593849528343224,0.5939879772923478
|
||||
B5_mofe_mlp,20260924,0.3/synchrony_async,0.16594815654028122,728,0.6153846153846154,0.5670250898329069,0.6416157484054565,0.859539120348063,0.5924952604080301
|
||||
|
@@ -0,0 +1,13 @@
|
||||
# R03: 按 math/Q2 V2 口径重训两种保留模型
|
||||
|
||||
## 假设
|
||||
|
||||
在保持 EarlyConcat + BiGRU 与 MoFE-7 + MLP Router 结构及共同监督目标不变的情况下，使用数学方案中的官方划分、连续块缺失训练和 42 个固定验证情景，可以公平比较两种模型的干净测试表现与缺失鲁棒性。
|
||||
|
||||
## 唯一实验改动
|
||||
|
||||
相对现有检查点，本轮重新训练时将缺失训练改为 0/10/30/50/70% 与 single/sync/partial/async，每个被选模态至少保留 20% 观测；训练和批次顺序在两个模型间配对。数学方案中的 C5 概率损失不适用于现有确定性分类/回归头，因此保留项目既有的 CE + 0.5 SmoothL1 联合目标。
|
||||
|
||||
## 数据使用
|
||||
|
||||
标准化器只在官方训练集观测行上拟合；官方验证集只用于早停与缺失评估；官方测试集在全部检查点确定后做一次干净评估。
|
||||
BIN
Binary file not shown.
+7
@@ -0,0 +1,7 @@
|
||||
method,seed,epoch,train_loss,valid_selection_loss,valid_clean_loss
|
||||
B0_early_concat,20260924,1,1.0061404870616064,0.9110350304252499,0.9014195590228825
|
||||
B0_early_concat,20260924,2,0.8046501874923706,0.889426393004564,0.8862256545286912
|
||||
B0_early_concat,20260924,3,0.7282454095504902,0.8806566258708199,0.8769266769126222
|
||||
B0_early_concat,20260924,4,0.6743332914732121,0.9174083739846618,0.9197112072955121
|
||||
B0_early_concat,20260924,5,0.6134337760784008,0.9341701424711354,0.9390361531750187
|
||||
B0_early_concat,20260924,6,0.558312753284419,1.000857290330824,1.0128365755081177
|
||||
|
BIN
Binary file not shown.
+7
@@ -0,0 +1,7 @@
|
||||
method,seed,epoch,train_loss,valid_selection_loss,valid_clean_loss
|
||||
B5_mofe_mlp,20260924,1,1.0217058570296675,0.9436172379569692,0.9375626621665535
|
||||
B5_mofe_mlp,20260924,2,0.8520832823382484,0.9506990911213906,0.952043721964071
|
||||
B5_mofe_mlp,20260924,3,0.8015031770423606,0.8901680516345161,0.887631527015141
|
||||
B5_mofe_mlp,20260924,4,0.7390829468214953,0.9029482278850052,0.9031652598590642
|
||||
B5_mofe_mlp,20260924,5,0.6777735639501501,0.9294115293484467,0.9311579852313786
|
||||
B5_mofe_mlp,20260924,6,0.6290948126051161,0.9776710203060737,0.9763853563057198
|
||||
|
+3
@@ -0,0 +1,3 @@
|
||||
method,seed,best_epoch,n_test,accuracy,macro_f1,mae,rmse,pearson
|
||||
B0_early_concat,20260924,3,727,0.6740027510316369,0.6157432417472255,0.6623634099960327,0.8897308076984263,0.6585211684420424
|
||||
B5_mofe_mlp,20260924,3,727,0.6795048143053645,0.6048829559870884,0.6760958433151245,0.8979946869648381,0.6426699367924718
|
||||
|
+6
@@ -0,0 +1,6 @@
|
||||
comparison,metric,delta,bootstrap_ci_2p5,bootstrap_ci_97p5,bootstrap_probability_delta_gt_0,replicates,resampling_unit,paired,seed
|
||||
B5_mofe_mlp minus B0_early_concat,accuracy,0.005502063273727598,-0.02588999712195796,0.03394678025644185,0.617,1000,source video id,True,20260925
|
||||
B5_mofe_mlp minus B0_early_concat,macro_f1,-0.01086028576013709,-0.04748880693804554,0.021613230578814074,0.251,1000,source video id,True,20260925
|
||||
B5_mofe_mlp minus B0_early_concat,mae,0.013732433319091797,-0.006543658673763275,0.0352545291185379,0.916,1000,source video id,True,20260925
|
||||
B5_mofe_mlp minus B0_early_concat,rmse,0.008263879266411811,-0.01499332646297088,0.03268860651949909,0.762,1000,source video id,True,20260925
|
||||
B5_mofe_mlp minus B0_early_concat,pearson,-0.015851231649570696,-0.032304558903424575,0.0012594110305533422,0.036,1000,source video id,True,20260925
|
||||
|
+11
@@ -0,0 +1,11 @@
|
||||
method,metric,mean,sd_across_seeds,n_seeds
|
||||
B0_early_concat,accuracy,0.6740027510316369,0.0,1
|
||||
B0_early_concat,macro_f1,0.6157432417472255,0.0,1
|
||||
B0_early_concat,mae,0.6623634099960327,0.0,1
|
||||
B0_early_concat,rmse,0.8897308076984263,0.0,1
|
||||
B0_early_concat,pearson,0.6585211684420424,0.0,1
|
||||
B5_mofe_mlp,accuracy,0.6795048143053645,0.0,1
|
||||
B5_mofe_mlp,macro_f1,0.6048829559870884,0.0,1
|
||||
B5_mofe_mlp,mae,0.6760958433151245,0.0,1
|
||||
B5_mofe_mlp,rmse,0.8979946869648381,0.0,1
|
||||
B5_mofe_mlp,pearson,0.6426699367924718,0.0,1
|
||||
|
@@ -0,0 +1,3 @@
|
||||
method,parameters_total,parameters_trainable,best_epoch
|
||||
B0_early_concat,253124,253124,3
|
||||
B5_mofe_mlp,306523,306523,3
|
||||
|
@@ -0,0 +1,87 @@
|
||||
{
|
||||
"experiment": "Retrained EarlyConcat and MoFE-7 + MLP Router using math/Q2 V2-compatible protocol",
|
||||
"created_unix": 1790293163.7924957,
|
||||
"device": "cuda",
|
||||
"cuda_device": "NVIDIA GeForce RTX 5070 Ti",
|
||||
"feature_file": "/home/gloamxun/modeling_zhaocui/E\u9898\u6570\u636e/\u9644\u4ef62-\u6570\u636e\u96c6\u7279\u5f81\u6587\u4ef6/aligned_50.pkl",
|
||||
"feature_sha256": "66e867aa74bc70a844e806e5571e371c9abb4a35f9e2887ce9b4d97ff2cb8fcd",
|
||||
"representation": "official aligned_50 ordered positions; not Q1 physical-time bins",
|
||||
"train_valid_test_counts": {
|
||||
"train": 3395,
|
||||
"valid": 728,
|
||||
"test": 727
|
||||
},
|
||||
"source_video_groups": {
|
||||
"train": 1528,
|
||||
"valid": 239,
|
||||
"test": 381
|
||||
},
|
||||
"official_group_splits_disjoint": true,
|
||||
"train_only_scaler": "/home/gloamxun/modeling_zhaocui/deep_learning/Q2/outputs/followups/R03_math_protocol_retraining/aligned_robust_stats.npz",
|
||||
"scaler_fit": "median and 1.4826*MAD on observed training rows only; zero-MAD fallback to std then 1",
|
||||
"seed": 20260924,
|
||||
"model_seeds": [
|
||||
20260924
|
||||
],
|
||||
"training_configuration": {
|
||||
"epoch_limit": 12,
|
||||
"early_stopping_patience": 3,
|
||||
"batch_size": 64,
|
||||
"optimizer": "AdamW",
|
||||
"learning_rate": 0.0003,
|
||||
"weight_decay": 0.001,
|
||||
"gradient_clip_norm": 1.0,
|
||||
"early_stopping_metric": "mean validation joint CE + 0.5*SmoothL1 over 0.0/none, 0.3/single, 0.3/sync, 0.5/async",
|
||||
"architecture_preserved": {
|
||||
"B0_early_concat": "EarlyConcat + BiGRU",
|
||||
"B5_mofe_mlp": "MoFE-7 + MLP Router"
|
||||
},
|
||||
"objective": "cross entropy + 0.5 * SmoothL1(intensity/3, label/3); same objective for both methods",
|
||||
"training_corruption": {
|
||||
"rates": [
|
||||
0.0,
|
||||
0.1,
|
||||
0.3,
|
||||
0.5,
|
||||
0.7
|
||||
],
|
||||
"patterns": [
|
||||
"single",
|
||||
"sync",
|
||||
"partial",
|
||||
"async"
|
||||
],
|
||||
"preserve_at_least_fraction_per_selected_modality": 0.2,
|
||||
"generator_seed": 20261227,
|
||||
"same_sample_masks_and_batch_orders_across_models": true
|
||||
}
|
||||
},
|
||||
"validation_protocol": {
|
||||
"scenario_seed": 20261833,
|
||||
"scenario_count": 42,
|
||||
"same_fixed_masks_for_both_models": true,
|
||||
"scenario_design": "math/Q2 42 controlled continuous-mask scenarios regenerated on each sample's original observation mask",
|
||||
"selection_scenarios": [
|
||||
"0.0/none",
|
||||
"0.3/single",
|
||||
"0.3/sync",
|
||||
"0.5/async"
|
||||
],
|
||||
"selection_note": "Deterministic-model adaptation; uses joint supervised loss instead of C5's probabilistic selection NLL.",
|
||||
"aurc": "normalized trapezoidal MAE area over realized equal-modality-weighted additional missing rate for single/sync/partial/async at 0/.1/.3/.5/.7"
|
||||
},
|
||||
"test_protocol": {
|
||||
"official_test_final_clean_passes": 1,
|
||||
"test_used_for_training_or_checkpoint_selection": false,
|
||||
"metrics": [
|
||||
"accuracy",
|
||||
"macro_f1",
|
||||
"mae",
|
||||
"rmse",
|
||||
"pearson"
|
||||
],
|
||||
"paired_group_bootstrap_replicates": 1000,
|
||||
"bootstrap_unit": "source video id",
|
||||
"bootstrap_seed": 20260925
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
method,seed,epoch,train_loss,valid_selection_loss,valid_clean_loss
|
||||
B0_early_concat,20260924,1,1.0061404870616064,0.9110350304252499,0.9014195590228825
|
||||
B0_early_concat,20260924,2,0.8046501874923706,0.889426393004564,0.8862256545286912
|
||||
B0_early_concat,20260924,3,0.7282454095504902,0.8806566258708199,0.8769266769126222
|
||||
B0_early_concat,20260924,4,0.6743332914732121,0.9174083739846618,0.9197112072955121
|
||||
B0_early_concat,20260924,5,0.6134337760784008,0.9341701424711354,0.9390361531750187
|
||||
B0_early_concat,20260924,6,0.558312753284419,1.000857290330824,1.0128365755081177
|
||||
B5_mofe_mlp,20260924,1,1.0217058570296675,0.9436172379569692,0.9375626621665535
|
||||
B5_mofe_mlp,20260924,2,0.8520832823382484,0.9506990911213906,0.952043721964071
|
||||
B5_mofe_mlp,20260924,3,0.8015031770423606,0.8901680516345161,0.887631527015141
|
||||
B5_mofe_mlp,20260924,4,0.7390829468214953,0.9029482278850052,0.9031652598590642
|
||||
B5_mofe_mlp,20260924,5,0.6777735639501501,0.9294115293484467,0.9311579852313786
|
||||
B5_mofe_mlp,20260924,6,0.6290948126051161,0.9776710203060737,0.9763853563057198
|
||||
|
+41
@@ -0,0 +1,41 @@
|
||||
method,seed,rate_mode,sample_epoch_assignments
|
||||
B0_early_concat,20260924,0.0/async,1034
|
||||
B0_early_concat,20260924,0.0/partial,1074
|
||||
B0_early_concat,20260924,0.0/single,1084
|
||||
B0_early_concat,20260924,0.0/sync,1065
|
||||
B0_early_concat,20260924,0.1/async,1059
|
||||
B0_early_concat,20260924,0.1/partial,1029
|
||||
B0_early_concat,20260924,0.1/single,1034
|
||||
B0_early_concat,20260924,0.1/sync,969
|
||||
B0_early_concat,20260924,0.3/async,1047
|
||||
B0_early_concat,20260924,0.3/partial,989
|
||||
B0_early_concat,20260924,0.3/single,978
|
||||
B0_early_concat,20260924,0.3/sync,1014
|
||||
B0_early_concat,20260924,0.5/async,1004
|
||||
B0_early_concat,20260924,0.5/partial,1017
|
||||
B0_early_concat,20260924,0.5/single,1013
|
||||
B0_early_concat,20260924,0.5/sync,986
|
||||
B0_early_concat,20260924,0.7/async,975
|
||||
B0_early_concat,20260924,0.7/partial,1006
|
||||
B0_early_concat,20260924,0.7/single,982
|
||||
B0_early_concat,20260924,0.7/sync,1011
|
||||
B5_mofe_mlp,20260924,0.0/async,1034
|
||||
B5_mofe_mlp,20260924,0.0/partial,1074
|
||||
B5_mofe_mlp,20260924,0.0/single,1084
|
||||
B5_mofe_mlp,20260924,0.0/sync,1065
|
||||
B5_mofe_mlp,20260924,0.1/async,1059
|
||||
B5_mofe_mlp,20260924,0.1/partial,1029
|
||||
B5_mofe_mlp,20260924,0.1/single,1034
|
||||
B5_mofe_mlp,20260924,0.1/sync,969
|
||||
B5_mofe_mlp,20260924,0.3/async,1047
|
||||
B5_mofe_mlp,20260924,0.3/partial,989
|
||||
B5_mofe_mlp,20260924,0.3/single,978
|
||||
B5_mofe_mlp,20260924,0.3/sync,1014
|
||||
B5_mofe_mlp,20260924,0.5/async,1004
|
||||
B5_mofe_mlp,20260924,0.5/partial,1017
|
||||
B5_mofe_mlp,20260924,0.5/single,1013
|
||||
B5_mofe_mlp,20260924,0.5/sync,986
|
||||
B5_mofe_mlp,20260924,0.7/async,975
|
||||
B5_mofe_mlp,20260924,0.7/partial,1006
|
||||
B5_mofe_mlp,20260924,0.7/single,982
|
||||
B5_mofe_mlp,20260924,0.7/sync,1011
|
||||
|
@@ -0,0 +1,9 @@
|
||||
# 后续实验输出
|
||||
|
||||
每项新实验在本目录下建立唯一子目录，例如 `F01_local_repair/`。把假设、运行配置、逐条件指标、统计比较、检查点和诊断图都放在该子目录中；不要覆盖已保留的参照权重与标准化参数：
|
||||
|
||||
```text
|
||||
../mofe_7experts/
|
||||
```
|
||||
|
||||
新实验的统一条件和记录要求见 [Q2 实验协议](../../EXPERIMENT_PROTOCOL.md)。
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
@@ -1,5 +1,5 @@
|
||||
[project]
|
||||
name = "deep-learning-q2-q3-selection"
|
||||
name = "deep-learning-q2"
|
||||
version = "0.1.0"
|
||||
requires-python = ">=3.14"
|
||||
dependencies = [
|
||||
@@ -7,7 +7,6 @@ dependencies = [
|
||||
"numpy>=2.5.3",
|
||||
"scikit-learn>=1.9.1",
|
||||
"torch>=2.14.0",
|
||||
"transformers>=5.17.0",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
|
||||
@@ -1 +1 @@
|
||||
"""Q2 robustness and Q3 explanation-selection experiments."""
|
||||
"""Q2 multimodal emotion-recognition experiments."""
|
||||
|
||||
@@ -0,0 +1,614 @@
|
||||
"""Score the frozen EarlyConcat and MoFE checkpoints using the math-Q2 protocol.
|
||||
|
||||
This script performs no training and selects no models. It evaluates the saved
|
||||
three-seed checkpoints on the official labeled test split once, and reuses the
|
||||
fixed 42-scenario validation-mask audit as the controlled-missingness protocol.
|
||||
All generated files stay under deep_learning/Q2/outputs/followups/.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import csv
|
||||
import argparse
|
||||
import hashlib
|
||||
import json
|
||||
import math
|
||||
import statistics
|
||||
import time
|
||||
from collections import defaultdict
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
from sklearn.metrics import accuracy_score, f1_score, mean_absolute_error, mean_squared_error
|
||||
from torch import nn
|
||||
|
||||
from .data import (
|
||||
ATTACHMENT2,
|
||||
MODALITIES,
|
||||
RobustStats,
|
||||
Split,
|
||||
_ids_and_targets,
|
||||
_text_mask,
|
||||
_unpickle,
|
||||
apply_robust_stats,
|
||||
fit_robust_stats,
|
||||
load_aligned,
|
||||
)
|
||||
from .models import AlignedFusionModel
|
||||
from .mofe import MixtureOfFusionExperts
|
||||
from .train_mofe import MODEL_CONFIG, _predict, _device_for, EARLYCONCAT, MOFE7_MLP
|
||||
|
||||
|
||||
Q2_ROOT = Path(__file__).resolve().parents[1]
|
||||
REPO_ROOT = Q2_ROOT.parents[1]
|
||||
REFERENCE_DIR = Q2_ROOT / "outputs" / "followups" / "R01_selected_model_reevaluation"
|
||||
OUTPUT_DIR = Q2_ROOT / "outputs" / "followups" / "R02_math_protocol_evaluation"
|
||||
SEEDS = (42, 3407, 2026)
|
||||
BOOTSTRAP_REPS = 1000
|
||||
TEST_BOOTSTRAP_SEED = 20260925
|
||||
AURC_BOOTSTRAP_SEED = 20260926
|
||||
SCENARIO_SEED = 20261833
|
||||
METHODS = (EARLYCONCAT, MOFE7_MLP)
|
||||
CURVE_MODES = ("single", "sync", "partial", "async")
|
||||
CURVE_RATES = (0.0, 0.1, 0.3, 0.5, 0.7)
|
||||
|
||||
|
||||
def write_csv(path: Path, rows: list[dict[str, Any]]) -> None:
|
||||
if not rows:
|
||||
return
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
fields = list(dict.fromkeys(key for row in rows for key in row))
|
||||
with path.open("w", newline="", encoding="utf-8-sig") as stream:
|
||||
writer = csv.DictWriter(stream, fieldnames=fields)
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
|
||||
|
||||
def sha256(path: Path) -> str:
|
||||
digest = hashlib.sha256()
|
||||
with path.open("rb") as stream:
|
||||
for block in iter(lambda: stream.read(1024 * 1024), b""):
|
||||
digest.update(block)
|
||||
return digest.hexdigest()
|
||||
|
||||
|
||||
def split_from_part(part: dict[str, Any]) -> Split:
|
||||
xs = tuple(np.asarray(part[name], dtype=np.float32) for name in MODALITIES)
|
||||
masks = [
|
||||
_text_mask(part),
|
||||
np.any(np.isfinite(xs[1]) & (xs[1] != 0), axis=-1),
|
||||
np.any(np.isfinite(xs[2]) & (xs[2] != 0), axis=-1),
|
||||
]
|
||||
ids, y_cls, y_reg = _ids_and_targets(part)
|
||||
return Split(xs, np.stack(masks, axis=-1), y_cls, y_reg, ids)
|
||||
|
||||
|
||||
def load_splits(feature_path: Path) -> dict[str, Split]:
|
||||
raw = _unpickle(feature_path)
|
||||
usual = load_aligned(feature_path)
|
||||
splits = {"train": usual["train"], "valid": usual["valid"], "test": split_from_part(raw["test"])}
|
||||
groups = {
|
||||
name: {sample_id.split("$_$", 1)[0] for sample_id in split.ids}
|
||||
for name, split in splits.items()
|
||||
}
|
||||
for first, second in (("train", "valid"), ("train", "test"), ("valid", "test")):
|
||||
overlap = groups[first] & groups[second]
|
||||
if overlap:
|
||||
raise ValueError(f"official {first}/{second} source-video groups overlap: {len(overlap)}")
|
||||
for name, split in splits.items():
|
||||
expected = np.where(split.y_reg < 0, 0, np.where(split.y_reg == 0, 1, 2))
|
||||
if not np.array_equal(expected, split.y_cls):
|
||||
raise ValueError(f"{name}: classification labels disagree with strict sign of regression labels")
|
||||
return splits
|
||||
|
||||
|
||||
def metrics(split: Split, logits: np.ndarray, intensity: np.ndarray, indices: np.ndarray | None = None) -> dict[str, float]:
|
||||
if indices is None:
|
||||
indices = np.arange(split.n)
|
||||
y_cls = split.y_cls[indices]
|
||||
y_reg = split.y_reg[indices]
|
||||
pred_cls = np.asarray(logits)[indices].argmax(axis=-1)
|
||||
pred_reg = np.clip(np.asarray(intensity).reshape(-1)[indices], -3.0, 3.0)
|
||||
return {
|
||||
"accuracy": float(accuracy_score(y_cls, pred_cls)),
|
||||
"macro_f1": float(f1_score(y_cls, pred_cls, labels=[0, 1, 2], average="macro", zero_division=0)),
|
||||
"mae": float(mean_absolute_error(y_reg, pred_reg)),
|
||||
"rmse": float(math.sqrt(mean_squared_error(y_reg, pred_reg))),
|
||||
"pearson": float(np.corrcoef(y_reg, pred_reg)[0, 1]) if np.std(y_reg) > 0 and np.std(pred_reg) > 0 else float("nan"),
|
||||
}
|
||||
|
||||
|
||||
def load_model(method: str, seed: int, dims: tuple[int, int, int], device: torch.device) -> nn.Module:
|
||||
if method == EARLYCONCAT:
|
||||
checkpoint = REFERENCE_DIR / "models" / "baselines" / "concat" / f"seed_{seed}" / "model_best.pt"
|
||||
model: nn.Module = AlignedFusionModel("concat", dims=dims).to(device)
|
||||
state = torch.load(checkpoint, map_location=device, weights_only=False)
|
||||
if state.get("kind") != "concat" or int(state.get("seed", -1)) != seed:
|
||||
raise ValueError(f"unexpected EarlyConcat checkpoint: {checkpoint}")
|
||||
elif method == MOFE7_MLP:
|
||||
checkpoint = REFERENCE_DIR / "models" / MOFE7_MLP / f"seed_{seed}" / "model_best.pt"
|
||||
model = MixtureOfFusionExperts(dims=dims, **MODEL_CONFIG).to(device)
|
||||
state = torch.load(checkpoint, map_location=device, weights_only=False)
|
||||
if state.get("config") != MODEL_CONFIG or int(state.get("seed", -1)) != seed:
|
||||
raise ValueError(f"unexpected MoFE checkpoint: {checkpoint}")
|
||||
else:
|
||||
raise ValueError(f"unknown model {method}")
|
||||
if tuple(state.get("dims", ())) != dims:
|
||||
raise ValueError(f"feature dimensions do not match checkpoint: {checkpoint}")
|
||||
model.load_state_dict(state["state_dict"])
|
||||
model.eval()
|
||||
return model
|
||||
|
||||
|
||||
def best_interval(visible: np.ndarray, wanted: int, cap: int, location: str, rng: np.random.Generator) -> tuple[int, int] | None:
|
||||
steps = len(visible)
|
||||
candidates: list[tuple[int, int, int, int]] = []
|
||||
for left in range(steps):
|
||||
hits = 0
|
||||
for right in range(left, steps):
|
||||
hits += int(visible[right])
|
||||
count = min(hits, cap)
|
||||
if count:
|
||||
candidates.append((abs(count - wanted), right - left + 1, left, right))
|
||||
if not candidates:
|
||||
return None
|
||||
best = min((error, span) for error, span, _, _ in candidates)
|
||||
tied = [(left, right) for error, span, left, right in candidates if (error, span) == best]
|
||||
if location == "start":
|
||||
return min(tied, key=lambda pair: (pair[0], pair[1]))
|
||||
if location == "end":
|
||||
return max(tied, key=lambda pair: (pair[1], pair[0]))
|
||||
if location == "middle":
|
||||
center = (steps - 1) / 2
|
||||
return min(tied, key=lambda pair: (abs((pair[0] + pair[1]) / 2 - center), pair[0]))
|
||||
if location != "random":
|
||||
raise ValueError(f"unknown interval location: {location}")
|
||||
return tied[int(rng.integers(0, len(tied)))]
|
||||
|
||||
|
||||
def spread_short_spans(visible: np.ndarray, wanted: int, cap: int) -> np.ndarray:
|
||||
positions = np.flatnonzero(visible)
|
||||
count = min(int(wanted), int(cap), len(positions))
|
||||
chosen = np.zeros(len(visible), dtype=bool)
|
||||
if count <= 0:
|
||||
return chosen
|
||||
n_spans = min(3, count)
|
||||
chunks = np.array_split(positions, n_spans)
|
||||
allocations = [count // n_spans + int(i < count % n_spans) for i in range(n_spans)]
|
||||
for chunk, amount in zip(chunks, allocations):
|
||||
if amount <= 0 or len(chunk) == 0:
|
||||
continue
|
||||
amount = min(amount, len(chunk))
|
||||
start = max(0, (len(chunk) - amount) // 2)
|
||||
chosen[chunk[start:start + amount]] = True
|
||||
return chosen
|
||||
|
||||
|
||||
def continuous_mask(
|
||||
original: np.ndarray,
|
||||
rate: float,
|
||||
mode: str,
|
||||
rng: np.random.Generator,
|
||||
*,
|
||||
modalities: tuple[int, ...] | None = None,
|
||||
location: str = "random",
|
||||
span_structure: str = "long",
|
||||
) -> np.ndarray:
|
||||
"""Reproduce math/Q2 continuous masking on this model's observed positions."""
|
||||
observed = np.asarray(original, dtype=bool)
|
||||
result = observed.copy()
|
||||
if rate <= 0 or mode == "none":
|
||||
return result
|
||||
steps, modality_count = observed.shape
|
||||
present = [m for m in range(modality_count) if observed[:, m].any()]
|
||||
if not present:
|
||||
return result
|
||||
if modalities is not None:
|
||||
selected = [int(m) for m in modalities if int(m) in present]
|
||||
if not selected:
|
||||
return result
|
||||
elif mode == "single":
|
||||
selected = [int(rng.choice(present))]
|
||||
elif mode in {"sync", "partial", "async"}:
|
||||
if len(present) == 1:
|
||||
selected = present
|
||||
else:
|
||||
count = int(rng.integers(2, min(3, len(present)) + 1))
|
||||
selected = sorted(int(v) for v in rng.choice(present, size=count, replace=False))
|
||||
else:
|
||||
raise ValueError(f"unknown mask mode: {mode}")
|
||||
|
||||
def max_hide(modality: int) -> int:
|
||||
count = int(observed[:, modality].sum())
|
||||
keep = max(1, int(math.ceil(0.2 * count)))
|
||||
return max(0, count - keep)
|
||||
|
||||
target = {m: min(max_hide(m), int(round(rate * int(observed[:, m].sum())))) for m in selected}
|
||||
if mode == "sync":
|
||||
span = max(1, int(round(rate * steps)))
|
||||
if location == "start":
|
||||
left = 0
|
||||
elif location == "end":
|
||||
left = steps - span
|
||||
elif location == "middle":
|
||||
left = (steps - span) // 2
|
||||
elif location == "random":
|
||||
left = int(rng.integers(0, max(1, steps - span + 1)))
|
||||
else:
|
||||
raise ValueError(f"unknown interval location: {location}")
|
||||
right = min(steps - 1, left + span - 1)
|
||||
for m in selected:
|
||||
candidates = np.flatnonzero(observed[left:right + 1, m]) + left
|
||||
amount = min(len(candidates), max_hide(m), target[m])
|
||||
if amount:
|
||||
offset = 0 if location != "end" else len(candidates) - amount
|
||||
result[candidates[max(0, offset):max(0, offset) + amount], m] = False
|
||||
else:
|
||||
common_span = max(1, int(round(rate * steps)))
|
||||
for rank, m in enumerate(selected):
|
||||
wanted = target[m]
|
||||
if wanted <= 0:
|
||||
continue
|
||||
cap = max_hide(m)
|
||||
if span_structure == "multi_short":
|
||||
hide = spread_short_spans(observed[:, m], wanted, cap)
|
||||
elif span_structure != "long":
|
||||
raise ValueError(f"unknown span structure: {span_structure}")
|
||||
elif mode == "single" and location != "random":
|
||||
# Place a contiguous block at the requested relative location
|
||||
# among observed positions, while keeping the selected-source
|
||||
# missing amount fixed. This avoids treating padding as time.
|
||||
interval = best_interval(observed[:, m], wanted, cap, location, rng)
|
||||
hide = np.zeros(steps, dtype=bool)
|
||||
if interval is not None:
|
||||
left, right = interval
|
||||
candidates = np.flatnonzero(observed[left:right + 1, m]) + left
|
||||
amount = min(len(candidates), wanted, cap)
|
||||
if amount:
|
||||
offset = 0 if location != "end" else len(candidates) - amount
|
||||
hide[candidates[max(0, offset):max(0, offset) + amount]] = True
|
||||
elif mode in {"partial", "async"}:
|
||||
if mode == "partial":
|
||||
base_left = int(rng.integers(0, max(1, steps - common_span + 1))) if location == "random" else (
|
||||
0 if location == "start" else steps - common_span if location == "end" else (steps - common_span) // 2
|
||||
)
|
||||
offset = int(round(rank * common_span * 0.5))
|
||||
else:
|
||||
base_left = 0 if location == "random" else (
|
||||
0 if location == "start" else steps - common_span if location == "end" else (steps - common_span) // 2
|
||||
)
|
||||
available = max(1, steps - common_span + 1)
|
||||
offsets = np.rint(np.linspace(0, max(0, available - 1), len(selected))).astype(int)
|
||||
if location == "random":
|
||||
rng.shuffle(offsets)
|
||||
offset = int(offsets[rank])
|
||||
left = min(max(0, base_left + offset), max(0, steps - common_span))
|
||||
right = min(steps - 1, left + common_span - 1)
|
||||
hide = np.zeros(steps, dtype=bool)
|
||||
candidates = np.flatnonzero(observed[left:right + 1, m]) + left
|
||||
amount = min(len(candidates), wanted, cap)
|
||||
if amount:
|
||||
hide[candidates[:amount]] = True
|
||||
else:
|
||||
interval = best_interval(observed[:, m], wanted, cap, location, rng)
|
||||
hide = np.zeros(steps, dtype=bool)
|
||||
if interval is not None:
|
||||
left, right = interval
|
||||
candidates = np.flatnonzero(observed[left:right + 1, m]) + left
|
||||
amount = min(len(candidates), wanted, cap)
|
||||
if amount:
|
||||
offset = 0 if location != "end" else len(candidates) - amount
|
||||
hide[candidates[max(0, offset):max(0, offset) + amount]] = True
|
||||
result[hide, m] = False
|
||||
return result
|
||||
|
||||
|
||||
def scenario_seed(seed: int, sample_id: str, key: str) -> int:
|
||||
return int.from_bytes(hashlib.sha256(f"{seed}:{sample_id}:{key}".encode()).digest()[:8], "little")
|
||||
|
||||
|
||||
def make_scenarios(valid: Split, seed: int = SCENARIO_SEED) -> dict[str, np.ndarray]:
|
||||
scenarios = {"0.0/none": valid.mask.copy()}
|
||||
for rate in CURVE_RATES[1:]:
|
||||
for mode in CURVE_MODES:
|
||||
key = f"{rate:.1f}/{mode}"
|
||||
scenarios[key] = np.stack([
|
||||
continuous_mask(mask, rate, mode, np.random.default_rng(scenario_seed(seed, sample_id, key)))
|
||||
for sample_id, mask in zip(valid.ids, valid.mask)
|
||||
])
|
||||
modality_sets = (((0,), "T"), ((1,), "A"), ((2,), "V"), ((0, 1), "TA"), ((0, 2), "TV"), ((1, 2), "AV"), ((0, 1, 2), "TAV"))
|
||||
for selected, label in modality_sets:
|
||||
key = f"0.3/modality_{label}"
|
||||
scenarios[key] = np.stack([
|
||||
continuous_mask(mask, 0.3, "sync", np.random.default_rng(scenario_seed(seed, sample_id, key)), modalities=selected)
|
||||
for sample_id, mask in zip(valid.ids, valid.mask)
|
||||
])
|
||||
for modality_index, label in enumerate(("T", "A", "V")):
|
||||
for location in ("start", "middle", "end"):
|
||||
key = f"0.3/location_{location}_{label}"
|
||||
scenarios[key] = np.stack([
|
||||
continuous_mask(mask, 0.3, "single", np.random.default_rng(scenario_seed(seed, sample_id, key)), modalities=(modality_index,), location=location)
|
||||
for sample_id, mask in zip(valid.ids, valid.mask)
|
||||
])
|
||||
for structure in ("long", "multi_short"):
|
||||
key = f"0.3/span_{structure}_{label}"
|
||||
scenarios[key] = np.stack([
|
||||
continuous_mask(mask, 0.3, "single", np.random.default_rng(scenario_seed(seed, sample_id, key)), modalities=(modality_index,), span_structure=structure)
|
||||
for sample_id, mask in zip(valid.ids, valid.mask)
|
||||
])
|
||||
for mode in ("sync", "partial", "async"):
|
||||
key = f"0.3/synchrony_{mode}"
|
||||
scenarios[key] = np.stack([
|
||||
continuous_mask(mask, 0.3, mode, np.random.default_rng(scenario_seed(seed, sample_id, key)), modalities=(0, 1, 2))
|
||||
for sample_id, mask in zip(valid.ids, valid.mask)
|
||||
])
|
||||
return scenarios
|
||||
|
||||
|
||||
def actual_additional_rates(base: np.ndarray, scenarios: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
|
||||
result = {}
|
||||
observed = base.sum(axis=1)
|
||||
for scenario, current in scenarios.items():
|
||||
newly_hidden = base & ~current
|
||||
hidden_count = newly_hidden.sum(axis=1)
|
||||
by_modality = np.divide(
|
||||
hidden_count,
|
||||
observed,
|
||||
out=np.full(hidden_count.shape, np.nan, dtype=np.float64),
|
||||
where=observed > 0,
|
||||
)
|
||||
result[scenario] = np.nanmean(by_modality, axis=1)
|
||||
return result
|
||||
|
||||
|
||||
def aurc_from_curve(rates: list[float], maes: list[float]) -> float:
|
||||
order = np.argsort(np.asarray(rates), kind="stable")
|
||||
x = np.asarray(rates, dtype=np.float64)[order]
|
||||
y = np.asarray(maes, dtype=np.float64)[order]
|
||||
unique_x, inverse = np.unique(x, return_inverse=True)
|
||||
unique_y = np.asarray([y[inverse == i].mean() for i in range(len(unique_x))])
|
||||
if len(unique_x) <= 1 or unique_x[-1] <= 0:
|
||||
return float(maes[0])
|
||||
return float(np.trapezoid(unique_y, unique_x) / unique_x[-1])
|
||||
|
||||
|
||||
def curve_scenarios(mode: str) -> list[str]:
|
||||
return ["0.0/none"] + [f"{rate:.1f}/{mode}" for rate in CURVE_RATES[1:]]
|
||||
|
||||
|
||||
def group_indices(ids: list[str]) -> tuple[list[str], dict[str, np.ndarray]]:
|
||||
groups = sorted({sample_id.split("$_$", 1)[0] for sample_id in ids})
|
||||
mapping = {group: np.flatnonzero(np.asarray([x.split("$_$", 1)[0] == group for x in ids])) for group in groups}
|
||||
return groups, mapping
|
||||
|
||||
|
||||
def bootstrap_clean_test(
|
||||
split: Split,
|
||||
preds: dict[tuple[str, int], dict[str, np.ndarray]],
|
||||
) -> list[dict[str, Any]]:
|
||||
groups, mapping = group_indices(split.ids)
|
||||
rng = np.random.default_rng(TEST_BOOTSTRAP_SEED)
|
||||
draws: dict[str, list[float]] = defaultdict(list)
|
||||
for _ in range(BOOTSTRAP_REPS):
|
||||
chosen = rng.choice(groups, size=len(groups), replace=True)
|
||||
indices = np.concatenate([mapping[group] for group in chosen])
|
||||
per_method = {}
|
||||
for method in METHODS:
|
||||
per_seed = [metrics(split, preds[(method, seed)]["logits"], preds[(method, seed)]["intensity"], indices) for seed in SEEDS]
|
||||
per_method[method] = {key: float(np.mean([row[key] for row in per_seed])) for key in per_seed[0]}
|
||||
for metric in per_method[EARLYCONCAT]:
|
||||
draws[metric].append(per_method[MOFE7_MLP][metric] - per_method[EARLYCONCAT][metric])
|
||||
rows = []
|
||||
for metric, values in draws.items():
|
||||
rows.append({
|
||||
"comparison": "MoFE-7 + MLP Router minus EarlyConcat + BiGRU",
|
||||
"metric": metric,
|
||||
"delta_mean_over_seeds": float(np.mean([r[metric] for r in [
|
||||
metrics(split, preds[(MOFE7_MLP, seed)]["logits"], preds[(MOFE7_MLP, seed)]["intensity"])
|
||||
for seed in SEEDS
|
||||
]]) - np.mean([r[metric] for r in [
|
||||
metrics(split, preds[(EARLYCONCAT, seed)]["logits"], preds[(EARLYCONCAT, seed)]["intensity"])
|
||||
for seed in SEEDS
|
||||
]])),
|
||||
"bootstrap_ci_2p5": float(np.quantile(values, 0.025)),
|
||||
"bootstrap_ci_97p5": float(np.quantile(values, 0.975)),
|
||||
"bootstrap_probability_delta_gt_0": float(np.mean(np.asarray(values) > 0)),
|
||||
"replicates": BOOTSTRAP_REPS,
|
||||
"resampling_unit": "source video id",
|
||||
"paired": True,
|
||||
"seed": TEST_BOOTSTRAP_SEED,
|
||||
})
|
||||
return rows
|
||||
|
||||
|
||||
def bootstrap_aurc(
|
||||
valid: Split,
|
||||
predictions: dict[tuple[str, int, str], dict[str, np.ndarray]],
|
||||
scenarios: dict[str, np.ndarray],
|
||||
rates_by_sample: dict[str, np.ndarray],
|
||||
) -> list[dict[str, Any]]:
|
||||
groups, mapping = group_indices(valid.ids)
|
||||
rng = np.random.default_rng(AURC_BOOTSTRAP_SEED)
|
||||
delta_by_mode: dict[str, list[float]] = {mode: [] for mode in CURVE_MODES}
|
||||
for _ in range(BOOTSTRAP_REPS):
|
||||
chosen = rng.choice(groups, size=len(groups), replace=True)
|
||||
indices = np.concatenate([mapping[group] for group in chosen])
|
||||
for mode in CURVE_MODES:
|
||||
keys = curve_scenarios(mode)
|
||||
model_aucs: dict[str, list[float]] = {method: [] for method in METHODS}
|
||||
for method in METHODS:
|
||||
for seed in SEEDS:
|
||||
xs = [float(np.nanmean(rates_by_sample[key][indices])) for key in keys]
|
||||
ys = [float(np.abs(valid.y_reg[indices] - predictions[(method, seed, key)]["intensity"][indices]).mean()) for key in keys]
|
||||
model_aucs[method].append(aurc_from_curve(xs, ys))
|
||||
delta_by_mode[mode].append(float(np.mean(model_aucs[MOFE7_MLP]) - np.mean(model_aucs[EARLYCONCAT])))
|
||||
point = {}
|
||||
for mode in CURVE_MODES:
|
||||
model_aucs = {}
|
||||
for method in METHODS:
|
||||
model_aucs[method] = []
|
||||
for seed in SEEDS:
|
||||
keys = curve_scenarios(mode)
|
||||
xs = [float(np.nanmean(rates_by_sample[key])) for key in keys]
|
||||
ys = [float(np.abs(valid.y_reg - predictions[(method, seed, key)]["intensity"]).mean()) for key in keys]
|
||||
model_aucs[method].append(aurc_from_curve(xs, ys))
|
||||
point[mode] = float(np.mean(model_aucs[MOFE7_MLP]) - np.mean(model_aucs[EARLYCONCAT]))
|
||||
rows = []
|
||||
for mode, values in delta_by_mode.items():
|
||||
rows.append({
|
||||
"mode": mode,
|
||||
"delta_aurc_mae_mofe_minus_earlyconcat": point[mode],
|
||||
"bootstrap_ci_2p5": float(np.quantile(values, 0.025)),
|
||||
"bootstrap_ci_97p5": float(np.quantile(values, 0.975)),
|
||||
"bootstrap_probability_delta_lt_0": float(np.mean(np.asarray(values) < 0)),
|
||||
"replicates": BOOTSTRAP_REPS,
|
||||
"resampling_unit": "source video id",
|
||||
"paired": True,
|
||||
"seed": AURC_BOOTSTRAP_SEED,
|
||||
})
|
||||
return rows
|
||||
|
||||
|
||||
def run(device_name: str = "auto", batch_size: int = 64, masks_only: bool = False) -> None:
|
||||
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
|
||||
device = _device_for(device_name)
|
||||
torch.set_num_threads(4)
|
||||
torch.backends.cudnn.deterministic = True
|
||||
torch.backends.cudnn.benchmark = False
|
||||
|
||||
feature_path = ATTACHMENT2 / "aligned_50.pkl"
|
||||
with (REFERENCE_DIR / "run_manifest.json").open("r", encoding="utf-8") as stream:
|
||||
reference_manifest = json.load(stream)
|
||||
if sha256(feature_path) != reference_manifest["feature_sha256"]:
|
||||
raise ValueError("current official feature file hash differs from the checkpoint evaluation manifest")
|
||||
|
||||
raw_splits = load_splits(feature_path)
|
||||
train = raw_splits["train"]
|
||||
valid = raw_splits["valid"]
|
||||
test = raw_splits["test"]
|
||||
scaler_path = REFERENCE_DIR / "aligned_robust_stats.npz"
|
||||
stats = RobustStats.load(scaler_path)
|
||||
computed = fit_robust_stats(train)
|
||||
scaler_diff = max(
|
||||
max(float(np.max(np.abs(a - b))) for a, b in zip(computed.center, stats.center)),
|
||||
max(float(np.max(np.abs(a - b))) for a, b in zip(computed.scale, stats.scale)),
|
||||
)
|
||||
if scaler_diff > 1e-6:
|
||||
raise ValueError(f"checkpoint scaler is not the train-only scaler (max difference {scaler_diff})")
|
||||
valid = apply_robust_stats(valid, stats)
|
||||
test = apply_robust_stats(test, stats)
|
||||
dims = tuple(x.shape[-1] for x in train.x)
|
||||
|
||||
if not masks_only:
|
||||
# Final, clean official-test evaluation; no retraining or selection occurs here.
|
||||
test_predictions: dict[tuple[str, int], dict[str, np.ndarray]] = {}
|
||||
test_rows: list[dict[str, Any]] = []
|
||||
for method in METHODS:
|
||||
for seed in SEEDS:
|
||||
model = load_model(method, seed, dims, device)
|
||||
prediction = _predict(model, test, test.mask, device, batch_size)
|
||||
test_predictions[(method, seed)] = prediction
|
||||
test_rows.append({"method": method, "seed": seed, "n_test": test.n, **metrics(test, prediction["logits"], prediction["intensity"])})
|
||||
del model
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
summary_rows = []
|
||||
for method in METHODS:
|
||||
subset = [row for row in test_rows if row["method"] == method]
|
||||
for metric in ("accuracy", "macro_f1", "mae", "rmse", "pearson"):
|
||||
values = [float(row[metric]) for row in subset]
|
||||
summary_rows.append({"method": method, "metric": metric, "mean": float(np.mean(values)), "sd_across_seeds": float(np.std(values, ddof=1))})
|
||||
write_csv(OUTPUT_DIR / "official_test_metrics_by_seed.csv", test_rows)
|
||||
write_csv(OUTPUT_DIR / "official_test_summary.csv", summary_rows)
|
||||
write_csv(OUTPUT_DIR / "official_test_paired_bootstrap.csv", bootstrap_clean_test(test, test_predictions))
|
||||
|
||||
# Reproduce the math-Q2 42-scenario design with a per-sample stable seed,
|
||||
# while applying it to the observation masks used to train these models.
|
||||
scenario_masks = make_scenarios(valid)
|
||||
rates_by_sample = actual_additional_rates(valid.mask, scenario_masks)
|
||||
condition_predictions: dict[tuple[str, int, str], dict[str, np.ndarray]] = {}
|
||||
condition_rows: list[dict[str, Any]] = []
|
||||
for method in METHODS:
|
||||
for seed in SEEDS:
|
||||
model = load_model(method, seed, dims, device)
|
||||
for scenario, masks in scenario_masks.items():
|
||||
prediction = _predict(model, valid, masks, device, batch_size)
|
||||
condition_predictions[(method, seed, scenario)] = prediction
|
||||
values = metrics(valid, prediction["logits"], prediction["intensity"])
|
||||
condition_rows.append({
|
||||
"method": method,
|
||||
"seed": seed,
|
||||
"scenario": scenario,
|
||||
"realized_additional_global_rate": float(np.nanmean(rates_by_sample[scenario])),
|
||||
"n_valid": valid.n,
|
||||
**values,
|
||||
})
|
||||
del model
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
write_csv(OUTPUT_DIR / "controlled_metrics_by_scenario.csv", condition_rows)
|
||||
|
||||
auc_rows: list[dict[str, Any]] = []
|
||||
for method in METHODS:
|
||||
for seed in SEEDS:
|
||||
for mode in CURVE_MODES:
|
||||
keys = curve_scenarios(mode)
|
||||
xs = [float(np.nanmean(rates_by_sample[key])) for key in keys]
|
||||
ys = [float(np.abs(valid.y_reg - condition_predictions[(method, seed, key)]["intensity"]).mean()) for key in keys]
|
||||
auc_rows.append({"method": method, "seed": seed, "mask_mode": mode, "aurc_mae": aurc_from_curve(xs, ys), "rates_realized": json.dumps(xs)})
|
||||
write_csv(OUTPUT_DIR / "aurc_mae_by_mode_seed.csv", auc_rows)
|
||||
auc_summary = []
|
||||
for method in METHODS:
|
||||
for mode in CURVE_MODES:
|
||||
values = [row["aurc_mae"] for row in auc_rows if row["method"] == method and row["mask_mode"] == mode]
|
||||
auc_summary.append({"method": method, "mask_mode": mode, "mean": float(np.mean(values)), "sd_across_seeds": float(np.std(values, ddof=1))})
|
||||
write_csv(OUTPUT_DIR / "aurc_mae_summary.csv", auc_summary)
|
||||
write_csv(OUTPUT_DIR / "aurc_mae_paired_bootstrap.csv", bootstrap_aurc(valid, condition_predictions, scenario_masks, rates_by_sample))
|
||||
|
||||
manifest = {
|
||||
"experiment": "Frozen EarlyConcat vs MoFE-7 evaluation under math/Q2 test protocol",
|
||||
"created_unix": time.time(),
|
||||
"device": str(device),
|
||||
"cuda_device": torch.cuda.get_device_name(0) if device.type == "cuda" else None,
|
||||
"feature_file": str(feature_path),
|
||||
"feature_sha256": sha256(feature_path),
|
||||
"representation": "official aligned_50 ordered positions; not physical-time bins",
|
||||
"train_valid_test_counts": {name: split.n for name, split in raw_splits.items()},
|
||||
"source_video_groups": {name: len({sample_id.split("$_$", 1)[0] for sample_id in split.ids}) for name, split in raw_splits.items()},
|
||||
"official_group_splits_disjoint": True,
|
||||
"test_evaluation": (
|
||||
"one final clean evaluation on official labeled test split; no training/model selection/calibration"
|
||||
if not masks_only else "test outputs preserved from the earlier single evaluation; no test prediction was rerun"
|
||||
),
|
||||
"test_prediction_performed_this_invocation": not masks_only,
|
||||
"seeds": list(SEEDS),
|
||||
"checkpoint_source": str(REFERENCE_DIR / "models"),
|
||||
"train_only_scaler": str(scaler_path),
|
||||
"scaler_max_abs_difference_from_train_refit": scaler_diff,
|
||||
"test_labels_used_for_training_or_selection": False,
|
||||
"controlled_missingness": {
|
||||
"scenario_seed": SCENARIO_SEED,
|
||||
"scenario_design": "math/Q2 42-scenario design regenerated on the Q2 models' BERT attention-mask base",
|
||||
"scenarios": len(scenario_masks),
|
||||
"AURC": "normalized trapezoidal area of MAE over realized equal-modality-weighted added missing rate, at 0/.1/.3/.5/.7 for single/sync/partial/async",
|
||||
},
|
||||
"bootstrap": {
|
||||
"replicates": BOOTSTRAP_REPS,
|
||||
"test_seed": TEST_BOOTSTRAP_SEED,
|
||||
"aurc_seed": AURC_BOOTSTRAP_SEED,
|
||||
"unit": "source video id",
|
||||
"paired": True,
|
||||
},
|
||||
}
|
||||
(OUTPUT_DIR / "run_manifest.json").write_text(json.dumps(manifest, indent=2), encoding="utf-8")
|
||||
print(f"wrote math-protocol comparison to {OUTPUT_DIR}")
|
||||
print(f"n_test={test.n}; n_valid={valid.n}; device={device}; scenarios={len(scenario_masks)}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--masks-only", action="store_true", help="Recompute validation mask scenarios without rerunning official-test inference")
|
||||
args = parser.parse_args()
|
||||
run(masks_only=args.masks_only)
|
||||
@@ -9,7 +9,7 @@ from .train_compare import _plot, _summary, _write_csv
|
||||
|
||||
def main() -> None:
|
||||
parser = argparse.ArgumentParser(description="Rebuild Q2 summary tables from saved validation predictions")
|
||||
parser.add_argument("--output-dir", default=str(Path(__file__).resolve().parents[1] / "outputs" / "algorithm_selection"))
|
||||
parser.add_argument("--output-dir", default=str(Path(__file__).resolve().parents[1] / "outputs" / "followups" / "earlyconcat_standalone"))
|
||||
args = parser.parse_args()
|
||||
output = Path(args.output_dir)
|
||||
with (output / "validation_metrics_by_condition.csv").open(encoding="utf-8-sig", newline="") as stream:
|
||||
|
||||
@@ -5,6 +5,8 @@ from torch import nn
|
||||
|
||||
|
||||
class AlignedFusionModel(nn.Module):
|
||||
"""Early concatenation + BiGRU model for the supplied aligned sequence."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
kind: str,
|
||||
@@ -14,8 +16,8 @@ class AlignedFusionModel(nn.Module):
|
||||
dropout: float = 0.15,
|
||||
) -> None:
|
||||
super().__init__()
|
||||
if kind not in {"concat", "gate", "crossattn"}:
|
||||
raise ValueError(f"unknown model kind: {kind}")
|
||||
if kind != "concat":
|
||||
raise ValueError(f"only the selected EarlyConcat model is maintained; got: {kind}")
|
||||
self.kind = kind
|
||||
self.hidden = hidden
|
||||
self.projections = nn.ModuleList(
|
||||
@@ -25,31 +27,9 @@ class AlignedFusionModel(nn.Module):
|
||||
self.position = nn.Parameter(torch.randn(1, steps, hidden) * 0.02)
|
||||
self.modality = nn.Parameter(torch.randn(1, 1, 3, hidden) * 0.02)
|
||||
self.dropout = nn.Dropout(dropout)
|
||||
|
||||
if kind == "concat":
|
||||
self.fusion = nn.Sequential(
|
||||
nn.Linear(hidden * 3 + 3, hidden), nn.GELU(), nn.LayerNorm(hidden), nn.Dropout(dropout)
|
||||
)
|
||||
elif kind == "gate":
|
||||
self.gate_score = nn.Sequential(nn.Linear(hidden, hidden // 2), nn.Tanh(), nn.Linear(hidden // 2, 1))
|
||||
self.fusion = nn.Sequential(
|
||||
nn.Linear(hidden + 3, hidden), nn.GELU(), nn.LayerNorm(hidden), nn.Dropout(dropout)
|
||||
)
|
||||
else:
|
||||
layer = nn.TransformerEncoderLayer(
|
||||
d_model=hidden,
|
||||
nhead=4,
|
||||
dim_feedforward=hidden * 2,
|
||||
dropout=dropout,
|
||||
activation="gelu",
|
||||
batch_first=True,
|
||||
norm_first=True,
|
||||
)
|
||||
self.cross_encoder = nn.TransformerEncoder(layer, num_layers=2, enable_nested_tensor=False)
|
||||
self.fusion = nn.Sequential(
|
||||
nn.Linear(hidden + 3, hidden), nn.GELU(), nn.LayerNorm(hidden), nn.Dropout(dropout)
|
||||
)
|
||||
|
||||
self.fusion = nn.Sequential(
|
||||
nn.Linear(hidden * 3 + 3, hidden), nn.GELU(), nn.LayerNorm(hidden), nn.Dropout(dropout)
|
||||
)
|
||||
self.temporal = nn.GRU(
|
||||
input_size=hidden,
|
||||
hidden_size=hidden // 2,
|
||||
@@ -72,38 +52,16 @@ class AlignedFusionModel(nn.Module):
|
||||
encoded.append(token)
|
||||
stack = torch.stack(encoded, dim=2) # B x T x M x D
|
||||
availability = masks.to(stack.dtype)
|
||||
gate_weights = None
|
||||
|
||||
if self.kind == "concat":
|
||||
fused = self.fusion(torch.cat((stack.flatten(2), availability), dim=-1))
|
||||
elif self.kind == "gate":
|
||||
scores = self.gate_score(stack).squeeze(-1)
|
||||
scores = scores.masked_fill(~masks, -1e4)
|
||||
gate_weights = torch.softmax(scores, dim=-1) * availability
|
||||
gate_weights = gate_weights / gate_weights.sum(dim=-1, keepdim=True).clamp_min(1e-8)
|
||||
weighted = (stack * gate_weights[..., None]).sum(dim=2)
|
||||
fused = self.fusion(torch.cat((weighted, availability), dim=-1))
|
||||
else:
|
||||
batch, steps, modalities, hidden = stack.shape
|
||||
flat = stack.reshape(batch, steps * modalities, hidden)
|
||||
valid = masks.reshape(batch, steps * modalities).clone()
|
||||
empty = ~valid.any(dim=1)
|
||||
if empty.any():
|
||||
valid[empty, 0] = True
|
||||
flat[empty, 0] = 0.0
|
||||
attended = self.cross_encoder(flat, src_key_padding_mask=~valid)
|
||||
attended = attended.reshape(batch, steps, modalities, hidden)
|
||||
observed_count = availability.sum(dim=2, keepdim=True)
|
||||
pooled = (attended * availability[..., None]).sum(dim=2) / observed_count.clamp_min(1.0)
|
||||
fused = self.fusion(torch.cat((pooled, availability), dim=-1))
|
||||
fused = self.fusion(torch.cat((stack.flatten(2), availability), dim=-1))
|
||||
|
||||
temporal, _ = self.temporal(self.dropout(fused))
|
||||
time_weight = masks.any(dim=-1).to(temporal.dtype)
|
||||
empty_time = time_weight.sum(dim=1, keepdim=True) <= 0
|
||||
if empty_time.any():
|
||||
time_weight[empty_time.squeeze(1), 0] = 1.0
|
||||
pooled = (temporal * time_weight[..., None]).sum(dim=1) / time_weight.sum(dim=1, keepdim=True).clamp_min(1.0)
|
||||
pooled = (temporal * time_weight[..., None]).sum(dim=1)
|
||||
pooled = pooled / time_weight.sum(dim=1, keepdim=True).clamp_min(1.0)
|
||||
hidden = self.head(pooled)
|
||||
logits = self.classifier(hidden)
|
||||
intensity = 3.0 * torch.tanh(self.regressor(hidden).squeeze(-1))
|
||||
return {"logits": logits, "intensity": intensity, "gate": gate_weights}
|
||||
return {"logits": logits, "intensity": intensity}
|
||||
|
||||
@@ -0,0 +1,224 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
from torch import nn
|
||||
|
||||
|
||||
SUBSETS: dict[str, tuple[int, ...]] = {
|
||||
"T": (0,),
|
||||
"A": (1,),
|
||||
"V": (2,),
|
||||
"TA": (0, 1),
|
||||
"TV": (0, 2),
|
||||
"AV": (1, 2),
|
||||
"TAV": (0, 1, 2),
|
||||
}
|
||||
EXPERT_NAMES = tuple(SUBSETS)
|
||||
EXPERT_BITS = {
|
||||
name: tuple(int(i in indices) for i in range(3))
|
||||
for name, indices in SUBSETS.items()
|
||||
}
|
||||
|
||||
|
||||
class MixtureOfFusionExperts(nn.Module):
|
||||
"""Seven-subset, hard-availability MoFE with the selected MLP router.
|
||||
|
||||
Each modality has a private projection. Experts only receive the private
|
||||
projections belonging to their subset. The weighted result is passed
|
||||
through one shared temporal backbone and one shared prediction head.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
dims: tuple[int, int, int],
|
||||
router: str = "mlp",
|
||||
expert_names: tuple[str, ...] = EXPERT_NAMES,
|
||||
availability_mode: str = "hard",
|
||||
steps: int = 50,
|
||||
latent_dim: int = 64,
|
||||
hidden: int = 128,
|
||||
dropout: float = 0.15,
|
||||
) -> None:
|
||||
super().__init__()
|
||||
if router != "mlp":
|
||||
raise ValueError(f"only the selected MLP router is maintained; got: {router}")
|
||||
if availability_mode != "hard":
|
||||
raise ValueError(f"only hard availability masking is maintained; got: {availability_mode}")
|
||||
if tuple(expert_names) != EXPERT_NAMES:
|
||||
raise ValueError("the selected MoFE uses all seven modality-subset experts")
|
||||
|
||||
self.dims = dims
|
||||
self.router_kind = router
|
||||
self.expert_names = tuple(expert_names)
|
||||
self.availability_mode = availability_mode
|
||||
self.steps = steps
|
||||
self.latent_dim = latent_dim
|
||||
self.hidden = hidden
|
||||
|
||||
# These projections are private to each modality and are not tied.
|
||||
self.private_projections = nn.ModuleList(
|
||||
nn.Sequential(nn.Linear(size, latent_dim), nn.GELU()) for size in dims
|
||||
)
|
||||
self.experts = nn.ModuleDict()
|
||||
for name in self.expert_names:
|
||||
n_modalities = len(SUBSETS[name])
|
||||
self.experts[name] = nn.Sequential(
|
||||
nn.Linear(n_modalities * latent_dim, hidden),
|
||||
nn.GELU(),
|
||||
nn.Dropout(dropout),
|
||||
nn.Linear(hidden, latent_dim),
|
||||
nn.LayerNorm(latent_dim),
|
||||
)
|
||||
|
||||
router_input_dim = 9
|
||||
self.router = nn.Sequential(
|
||||
nn.Linear(router_input_dim, 16),
|
||||
nn.GELU(),
|
||||
nn.Linear(16, len(self.expert_names)),
|
||||
)
|
||||
|
||||
# Shared early-fusion projection, BiGRU, and task heads.
|
||||
self.all_missing_token = nn.Parameter(torch.zeros(1, 1, latent_dim))
|
||||
self.input_projection = nn.Sequential(
|
||||
nn.Linear(latent_dim + 3, hidden),
|
||||
nn.GELU(),
|
||||
nn.LayerNorm(hidden),
|
||||
nn.Dropout(dropout),
|
||||
)
|
||||
self.dropout = nn.Dropout(dropout)
|
||||
self.temporal = nn.GRU(
|
||||
input_size=hidden,
|
||||
hidden_size=hidden // 2,
|
||||
num_layers=1,
|
||||
batch_first=True,
|
||||
bidirectional=True,
|
||||
)
|
||||
self.head = nn.Sequential(nn.Linear(hidden, hidden // 2), nn.GELU(), nn.Dropout(dropout))
|
||||
self.classifier = nn.Linear(hidden // 2, 3)
|
||||
self.regressor = nn.Linear(hidden // 2, 1)
|
||||
|
||||
@staticmethod
|
||||
def _availability(masks: torch.Tensor, names: tuple[str, ...]) -> torch.Tensor:
|
||||
masks = masks.bool()
|
||||
columns = [masks[..., list(SUBSETS[name])].all(dim=-1) for name in names]
|
||||
return torch.stack(columns, dim=-1)
|
||||
|
||||
def _router_features(
|
||||
self,
|
||||
private: tuple[torch.Tensor, torch.Tensor, torch.Tensor],
|
||||
masks: torch.Tensor,
|
||||
) -> torch.Tensor:
|
||||
observed = masks.to(dtype=private[0].dtype)
|
||||
magnitude = torch.stack(
|
||||
[torch.sqrt(x.square().mean(dim=-1) + 1e-8) for x in private], dim=-1
|
||||
)
|
||||
local_ratio = F.avg_pool1d(
|
||||
observed.transpose(1, 2), kernel_size=5, stride=1, padding=2, count_include_pad=False
|
||||
).transpose(1, 2)
|
||||
return torch.cat((observed, torch.log1p(magnitude), local_ratio), dim=-1)
|
||||
|
||||
def _route(
|
||||
self,
|
||||
router_features: torch.Tensor,
|
||||
availability: torch.Tensor,
|
||||
force_expert: str | None,
|
||||
) -> torch.Tensor:
|
||||
scores = self.router(router_features)
|
||||
scores = scores.masked_fill(~availability, -1e4)
|
||||
weights = torch.softmax(scores, dim=-1) * availability.to(scores.dtype)
|
||||
# In the full seven-expert model this is exactly the all-modalities-
|
||||
# missing case. It also safely handles ablations with no eligible set.
|
||||
has_expert = availability.any(dim=-1, keepdim=True)
|
||||
weights = weights * has_expert.to(weights.dtype)
|
||||
weights = weights / weights.sum(dim=-1, keepdim=True).clamp_min(1e-8)
|
||||
|
||||
if force_expert is not None:
|
||||
if force_expert not in self.expert_names:
|
||||
raise ValueError(f"expert {force_expert} is not enabled in this model")
|
||||
expert_idx = self.expert_names.index(force_expert)
|
||||
forced = torch.zeros_like(weights)
|
||||
forced[..., expert_idx] = 1.0
|
||||
# Force the requested expert where its modality subset is present;
|
||||
# where it is unavailable, use the learned router over eligible
|
||||
# experts instead of replacing observed information with zeros.
|
||||
return torch.where(availability[..., expert_idx, None], forced, weights)
|
||||
|
||||
return weights
|
||||
|
||||
def forward(
|
||||
self,
|
||||
xs: tuple[torch.Tensor, torch.Tensor, torch.Tensor],
|
||||
masks: torch.Tensor,
|
||||
force_expert: str | None = None,
|
||||
) -> dict[str, Any]:
|
||||
masks = masks.bool()
|
||||
if masks.ndim != 3 or masks.shape[-1] != 3:
|
||||
raise ValueError(f"masks must have shape B x T x 3, got {tuple(masks.shape)}")
|
||||
if masks.shape[1] > self.steps:
|
||||
raise ValueError(f"sequence has {masks.shape[1]} steps, model supports {self.steps}")
|
||||
|
||||
private_values = []
|
||||
for modality, (projector, x) in enumerate(zip(self.private_projections, xs)):
|
||||
projected = projector(x)
|
||||
projected = projected * masks[..., modality, None].to(projected.dtype)
|
||||
private_values.append(projected)
|
||||
private = tuple(private_values)
|
||||
router_features = self._router_features(private, masks)
|
||||
availability = self._availability(masks, self.expert_names)
|
||||
|
||||
local_expert_outputs = []
|
||||
for name in self.expert_names:
|
||||
indices = SUBSETS[name]
|
||||
expert_input = torch.cat([private[i] for i in indices], dim=-1)
|
||||
local_expert_outputs.append(self.experts[name](expert_input))
|
||||
expert_stack = torch.stack(local_expert_outputs, dim=-2)
|
||||
|
||||
alpha_local = self._route(router_features, availability, force_expert)
|
||||
fused = (expert_stack * alpha_local[..., None]).sum(dim=-2)
|
||||
has_expert = availability.any(dim=-1)
|
||||
fused = torch.where(
|
||||
has_expert[..., None], fused, self.all_missing_token.expand_as(fused)
|
||||
)
|
||||
|
||||
# Restore a stable seven-column interface for saved diagnostics,
|
||||
# including expert-set ablations.
|
||||
alpha = masks.new_zeros((*masks.shape[:2], len(EXPERT_NAMES)), dtype=private[0].dtype)
|
||||
expert_outputs = private[0].new_zeros((*masks.shape[:2], len(EXPERT_NAMES), self.latent_dim))
|
||||
for local_idx, name in enumerate(self.expert_names):
|
||||
global_idx = EXPERT_NAMES.index(name)
|
||||
alpha[..., global_idx] = alpha_local[..., local_idx]
|
||||
expert_outputs[..., global_idx, :] = expert_stack[..., local_idx, :]
|
||||
|
||||
fused_with_masks = torch.cat((fused, masks.to(fused.dtype)), dim=-1)
|
||||
encoded = self.input_projection(fused_with_masks)
|
||||
temporal, _ = self.temporal(self.dropout(encoded))
|
||||
time_weight = masks.any(dim=-1).to(temporal.dtype)
|
||||
empty_time = time_weight.sum(dim=1, keepdim=True) <= 0
|
||||
if empty_time.any():
|
||||
time_weight[empty_time.squeeze(1), 0] = 1.0
|
||||
pooled = (temporal * time_weight[..., None]).sum(dim=1)
|
||||
pooled = pooled / time_weight.sum(dim=1, keepdim=True).clamp_min(1.0)
|
||||
hidden = self.head(pooled)
|
||||
logits = self.classifier(hidden)
|
||||
intensity = 3.0 * torch.tanh(self.regressor(hidden).squeeze(-1))
|
||||
|
||||
bits = torch.tensor(
|
||||
[EXPERT_BITS[name] for name in EXPERT_NAMES],
|
||||
dtype=alpha.dtype,
|
||||
device=alpha.device,
|
||||
)
|
||||
utility = torch.einsum("bte,em->btm", alpha, bits)
|
||||
return {
|
||||
"logits": logits,
|
||||
"intensity": intensity,
|
||||
"fused": fused,
|
||||
"alpha": alpha,
|
||||
"utility": utility,
|
||||
"availability": availability,
|
||||
"expert_outputs": expert_outputs,
|
||||
"fallback": ~has_expert,
|
||||
"router_features": router_features,
|
||||
}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user