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加入实验输出（批次 12/14）

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gloamxun
2026-09-23 23:37:16 +08:00
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deep_learning/Q1/outputs/method_comparison/reconstruction_summary.csv
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method,target_modality,n,mae_standardized_mean,mae_standardized_std,smooth_l1_standardized_mean,smooth_l1_standardized_std
M1,text,5,0.8308010935783386,0.028634584948895196,0.4546235024929047,0.025151457325080215
M1,audio,5,0.6908806562423706,0.06720606353302543,0.34603241086006165,0.06541831705153776
M1,vision,5,0.9209612965583801,0.04009937912435952,0.5347834944725036,0.036821434614539225
M2,text,5,0.8190697312355042,0.03563334190353864,0.44534851908683776,0.030773561031959877
M2,audio,5,0.6621044635772705,0.05689547728439605,0.32293344140052793,0.05414120404134669
M2,vision,5,0.9195392370223999,0.03744298345037278,0.5340398073196411,0.0346960350528028
M3,text,15,0.8311106324195862,0.025205971351551344,0.45519693891207375,0.021717713583393992
M3,audio,15,0.38449583053588865,0.050754623523549675,0.14107545365889868,0.05381054674326515
M3,vision,15,0.868217929204305,0.03802189028391118,0.48890710473060606,0.03450529817617854
M4,text,15,0.4924671709537506,0.011169848357006705,0.18583014905452727,0.008262501869688806
M4,audio,15,0.37839911778767904,0.05503994105535867,0.13528098662694296,0.05838370221384358
M4,vision,15,0.8630666335423788,0.03867536107911695,0.48466227054595945,0.03512809212998346
1 method target_modality n mae_standardized_mean mae_standardized_std smooth_l1_standardized_mean smooth_l1_standardized_std
2 M1 text 5 0.8308010935783386 0.028634584948895196 0.4546235024929047 0.025151457325080215
3 M1 audio 5 0.6908806562423706 0.06720606353302543 0.34603241086006165 0.06541831705153776
4 M1 vision 5 0.9209612965583801 0.04009937912435952 0.5347834944725036 0.036821434614539225
5 M2 text 5 0.8190697312355042 0.03563334190353864 0.44534851908683776 0.030773561031959877
6 M2 audio 5 0.6621044635772705 0.05689547728439605 0.32293344140052793 0.05414120404134669
7 M2 vision 5 0.9195392370223999 0.03744298345037278 0.5340398073196411 0.0346960350528028
8 M3 text 15 0.8311106324195862 0.025205971351551344 0.45519693891207375 0.021717713583393992
9 M3 audio 15 0.38449583053588865 0.050754623523549675 0.14107545365889868 0.05381054674326515
10 M3 vision 15 0.868217929204305 0.03802189028391118 0.48890710473060606 0.03450529817617854
11 M4 text 15 0.4924671709537506 0.011169848357006705 0.18583014905452727 0.008262501869688806
12 M4 audio 15 0.37839911778767904 0.05503994105535867 0.13528098662694296 0.05838370221384358
13 M4 vision 15 0.8630666335423788 0.03867536107911695 0.48466227054595945 0.03512809212998346