{"id":"W4413145680","doi":"10.1109/cvpr52734.2025.02835","title":"Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Discriminative model; Computer science; Distillation; Artificial intelligence; Machine learning; Data mining; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000603433,0.0000895581,0.0001021862,0.0001132605,0.00003978559,0.00002989729,0.0001164554,0.00003641883,0.000006897629],"category_scores_gemma":[0.0000914005,0.00008447372,0.00001170979,0.0001491224,0.00002157709,0.0002426576,0.00004077874,0.00006517849,9.200485e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007547407,"about_ca_system_score_gemma":0.000007420559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001746847,"about_ca_topic_score_gemma":0.0001858191,"domain_scores_codex":[0.9995694,0.000005476107,0.0001236437,0.0001326343,0.00004141012,0.0001274688],"domain_scores_gemma":[0.9997172,0.00008239889,0.00001264056,0.0001578634,0.00001683254,0.00001303273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007439288,0.00007743297,0.001110149,0.0009628835,0.00004923418,0.000004855778,0.0005428319,0.0170675,0.01389952,0.05941391,0.5984917,0.3083056],"study_design_scores_gemma":[0.001627881,0.00007139034,0.02832642,0.0005635449,0.00003901139,0.00000423303,0.0006308215,0.4152588,0.05406207,0.07713228,0.421359,0.0009245034],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006987079,0.0001453332,0.9942197,0.0001827645,0.00005095864,0.0003211962,0.001430481,0.0004912287,0.002459676],"genre_scores_gemma":[0.7928628,0.00001666701,0.2002379,0.0001196258,0.00001533937,0.00007795785,0.006576067,0.00001574633,0.00007790415],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7939818,"threshold_uncertainty_score":0.3444738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02596796499657976,"score_gpt":0.3380869598624544,"score_spread":0.3121189948658746,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}