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+method,mvr_text,entropy_text,trajectory_span_text,mvr_audio,entropy_audio,trajectory_span_audio,mvr_vision,entropy_vision,trajectory_span_vision,r_at_1_text_to_audio,r_at_5_text_to_audio,r_at_1_text_to_vision,r_at_5_text_to_vision,reconstruction_mae_text,reconstruction_mae_audio,reconstruction_mae_vision,emotion_accuracy,emotion_macro_f1,emotion_mae,emotion_pearson
+M1,0.0,0.0008249471336603165,0.8612861529795919,0.0,0.35824004098773005,0.8937758523714728,0.0,0.02091189981205389,0.8956127409730107,0.0012000000569969416,0.007000000309199094,0.0020000000949949026,0.007000000402331352,0.8308010935783386,0.6908806562423706,0.9209612965583801,0.5900000000000001,0.43700352733686065,0.5521364179253578,0.5305163430956757
+M2,0.0,0.003971234038472176,0.8611038638930768,0.0,0.39199826538562776,0.968455815287307,0.0,0.015714890849776567,0.9744537002407014,0.0014000000432133675,0.009200000390410423,0.003600000194273889,0.008800000487826764,0.8190697312355042,0.6621044635772705,0.9195392370223999,0.55,0.3434301254301254,0.5691992919147014,0.5082439027512137
+M3,0.0,0.0004981429129838944,0.8611844960658346,0.01857142824679613,0.992265993754069,-0.001562372346719104,0.06843537279715141,0.9827406370639801,-0.004611149926980335,0.01966666733690848,0.043000001646578315,0.0062666668944681685,0.013800000709791978,0.8311106324195862,0.38449583053588865,0.868217929204305,0.5766666666666667,0.43789820467598245,0.5534388141334057,0.5457241196963684
+M4,0.0,0.9999777108430863,0.00020046850045522113,0.0,0.9999900078773498,4.607309897740703e-05,0.0,0.9999960112571716,0.00010548800230026034,0.007066666963510215,0.01226666709408164,0.0016000000604738792,0.00760000046963493,0.4924671709537506,0.37839911778767904,0.8630666335423788,0.56,0.41446068467573843,0.6231901267170906,0.5067829543507287
diff --git a/deep_learning/Q1/outputs/method_comparison/emotion_summary.csv b/deep_learning/Q1/outputs/method_comparison/emotion_summary.csv
new file mode 100644
index 0000000..c67f0d5
--- /dev/null
+++ b/deep_learning/Q1/outputs/method_comparison/emotion_summary.csv
@@ -0,0 +1,5 @@
+method,n,accuracy_mean,accuracy_std,macro_f1_mean,macro_f1_std,mae_mean,mae_std,pearson_mean,pearson_std
+M1,5,0.5900000000000001,0.1673320053068151,0.43700352733686065,0.22785227549938045,0.5521364179253578,0.12144893660249381,0.5305163430956757,0.09576372130151391
+M2,5,0.55,0.1767766952966369,0.3434301254301254,0.14084701638388486,0.5691992919147014,0.11997495602498047,0.5082439027512137,0.09789171743073
+M3,15,0.5766666666666667,0.18503538915054937,0.43789820467598245,0.21990438278507196,0.5534388141334057,0.11230839313313754,0.5457241196963684,0.09265676731571848
+M4,15,0.56,0.15142183273415838,0.41446068467573843,0.13578816810911878,0.6231901267170906,0.13326862372482587,0.5067829543507287,0.1021700904550588
diff --git a/deep_learning/Q1/outputs/method_comparison/experiment.log b/deep_learning/Q1/outputs/method_comparison/experiment.log
new file mode 100644
index 0000000..0abfd16
--- /dev/null
+++ b/deep_learning/Q1/outputs/method_comparison/experiment.log
@@ -0,0 +1,129 @@
+[start] samples=100 groups=37 folds=5 seeds=[42, 3407, 2026] device=cuda
+[fold 1/5] train=80 validation=20 train_video_ids=31 validation_video_ids=6
+[fold 1] evaluate M1 and train identical probes
+[fold 1] evaluate M2 and train identical probes
+[fold 1] train M3, seed=42
+In file included from /usr/include/python3.14/pyconfig.h:6,
+                 from /usr/include/python3.14/Python.h:14,
+                 from /home/gloamxun/modeling_zhaocui/Q1/.venv/lib/python3.14/site-packages/triton/backends/nvidia/driver.c:9:
+/usr/include/python3.14/pyconfig-64.h:2031:9: warning: ‘_POSIX_C_SOURCE’ redefined
+ 2031 | #define _POSIX_C_SOURCE 200809L
+      |         ^~~~~~~~~~~~~~~
+In file included from /usr/include/bits/libc-header-start.h:33,
+                 from /usr/include/stdlib.h:26,
+                 from /home/gloamxun/modeling_zhaocui/Q1/.venv/lib/python3.14/site-packages/triton/backends/nvidia/include/cuda.h:56,
+                 from /home/gloamxun/modeling_zhaocui/Q1/.venv/lib/python3.14/site-packages/triton/backends/nvidia/driver.c:1:
+/usr/include/features.h:319:10: note: this is the location of the previous definition
+  319 | # define _POSIX_C_SOURCE        202405L
+      |          ^~~~~~~~~~~~~~~
+[fold 1] M3, seed=42 best_epoch=50 val_objective=4.93766; running frozen probes
+[fold 1] train M4, seed=42
+[fold 1] M4, seed=42 best_epoch=4 val_objective=6.07687; running frozen probes
+[fold 1] train M3, seed=3407
+[fold 1] M3, seed=3407 best_epoch=50 val_objective=4.98259; running frozen probes
+[fold 1] train M4, seed=3407
+[fold 1] M4, seed=3407 best_epoch=4 val_objective=5.87185; running frozen probes
+[fold 1] train M3, seed=2026
+[fold 1] M3, seed=2026 best_epoch=50 val_objective=5.10248; running frozen probes
+[fold 1] train M4, seed=2026
+[fold 1] M4, seed=2026 best_epoch=3 val_objective=6.09901; running frozen probes
+[fold 2/5] train=80 validation=20 train_video_ids=30 validation_video_ids=7
+[fold 2] evaluate M1 and train identical probes
+[fold 2] evaluate M2 and train identical probes
+[fold 2] train M3, seed=42
+[fold 2] M3, seed=42 best_epoch=1 val_objective=6.12588; running frozen probes
+[fold 2] train M4, seed=42
+[fold 2] M4, seed=42 best_epoch=1 val_objective=5.94268; running frozen probes
+[fold 2] train M3, seed=3407
+[fold 2] M3, seed=3407 best_epoch=50 val_objective=5.14454; running frozen probes
+[fold 2] train M4, seed=3407
+[fold 2] M4, seed=3407 best_epoch=3 val_objective=6.06774; running frozen probes
+[fold 2] train M3, seed=2026
+[fold 2] M3, seed=2026 best_epoch=50 val_objective=5.17416; running frozen probes
+[fold 2] train M4, seed=2026
+[fold 2] M4, seed=2026 best_epoch=1 val_objective=5.96431; running frozen probes
+[fold 3/5] train=80 validation=20 train_video_ids=29 validation_video_ids=8
+[fold 3] evaluate M1 and train identical probes
+[fold 3] evaluate M2 and train identical probes
+[fold 3] train M3, seed=42
+[fold 3] M3, seed=42 best_epoch=50 val_objective=4.97643; running frozen probes
+[fold 3] train M4, seed=42
+[fold 3] M4, seed=42 best_epoch=3 val_objective=6.19582; running frozen probes
+[fold 3] train M3, seed=3407
+[fold 3] M3, seed=3407 best_epoch=50 val_objective=4.65949; running frozen probes
+[fold 3] train M4, seed=3407
+[fold 3] M4, seed=3407 best_epoch=9 val_objective=5.91066; running frozen probes
+[fold 3] train M3, seed=2026
+[fold 3] M3, seed=2026 best_epoch=50 val_objective=4.99993; running frozen probes
+[fold 3] train M4, seed=2026
+[fold 3] M4, seed=2026 best_epoch=3 val_objective=6.02409; running frozen probes
+[fold 4/5] train=80 validation=20 train_video_ids=29 validation_video_ids=8
+[fold 4] evaluate M1 and train identical probes
+[fold 4] evaluate M2 and train identical probes
+[fold 4] train M3, seed=42
+[fold 4] M3, seed=42 best_epoch=50 val_objective=5.15230; running frozen probes
+[fold 4] train M4, seed=42
+[fold 4] M4, seed=42 best_epoch=1 val_objective=5.99857; running frozen probes
+[fold 4] train M3, seed=3407
+[fold 4] M3, seed=3407 best_epoch=50 val_objective=5.09800; running frozen probes
+[fold 4] train M4, seed=3407
+[fold 4] M4, seed=3407 best_epoch=2 val_objective=6.03456; running frozen probes
+[fold 4] train M3, seed=2026
+[fold 4] M3, seed=2026 best_epoch=50 val_objective=5.26026; running frozen probes
+[fold 4] train M4, seed=2026
+[fold 4] M4, seed=2026 best_epoch=2 val_objective=6.08121; running frozen probes
+[fold 5/5] train=80 validation=20 train_video_ids=29 validation_video_ids=8
+[fold 5] evaluate M1 and train identical probes
+[fold 5] evaluate M2 and train identical probes
+[fold 5] train M3, seed=42
+[fold 5] M3, seed=42 best_epoch=50 val_objective=5.29874; running frozen probes
+[fold 5] train M4, seed=42
+[fold 5] M4, seed=42 best_epoch=4 val_objective=6.02189; running frozen probes
+[fold 5] train M3, seed=3407
+[fold 5] M3, seed=3407 best_epoch=50 val_objective=4.95355; running frozen probes
+[fold 5] train M4, seed=3407
+[fold 5] M4, seed=3407 best_epoch=8 val_objective=6.05872; running frozen probes
+[fold 5] train M3, seed=2026
+[fold 5] M3, seed=2026 best_epoch=50 val_objective=5.13369; running frozen probes
+[fold 5] train M4, seed=2026
+[fold 5] M4, seed=2026 best_epoch=1 val_objective=5.88269; running frozen probes
+[done] elapsed_seconds=516.3 output=/home/gloamxun/modeling_zhaocui/Q1/outputs/method_comparison
+{
+  "created_utc": "2026-09-23T09:07:49.626404+00:00",
+  "sample_count": 100,
+  "group_count": 37,
+  "folds": 5,
+  "seeds": [
+    42,
+    3407,
+    2026
+  ],
+  "device": "cuda",
+  "gpu_name": "NVIDIA GeForce RTX 5070 Ti",
+  "python": "3.14.7",
+  "torch": "2.14.0+cu130",
+  "parameters": {
+    "grid_size": 50,
+    "hidden_size": 128,
+    "heads": 4,
+    "dropout": 0.1,
+    "batch_size": 8,
+    "epochs_max": 50,
+    "early_stopping_patience": 8,
+    "learning_rate": 0.0001,
+    "mask_ratio": 0.2,
+    "retrieval_probe_epochs": 20,
+    "reconstruction_probe_epochs": 25,
+    "mvr_epsilon": 0.02
+  },
+  "objective": "masked reconstruction + cross-modal contrastive + temporal monotonicity; emotion labels unused",
+  "split_rule": "GroupKFold by group_id/video_id",
+  "example_sample_id": "-tPCytz4rww/12",
+  "elapsed_seconds": 516.2944533824921,
+  "interpretation_limits": [
+    "Grid-index retrieval is a representation-consistency probe, not independent temporal ground truth.",
+    "Masked reconstruction uses a decoder trained on the training fold and reports standardized-feature errors.",
+    "The emotion probe is a small-sample downstream utility check, not a claim of generalization to MOSEI.",
+    "No human event timestamps are available, so human IoU/MATE is not reported."
+  ]
+}
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