{"id":"W4390873538","doi":"10.1109/iccv51070.2023.00166","title":"Parametric Information Maximization for Generalized Category Discovery","year":2023,"lang":"en","type":"article","venue":"","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Thales (Canada)","funders":"","keywords":"Parameterized complexity; Maximization; Computer science; Parametric statistics; Mutual information; Class (philosophy); Code (set theory); Data mining; Nonparametric statistics; Artificial intelligence; Theoretical computer science; Machine learning; Algorithm; Mathematics; Mathematical optimization; Statistics; Set (abstract data type); Programming language","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":[0.0001433308,0.00005834184,0.00006118869,0.0004245253,0.00008417819,0.0003547833,0.000384684,0.00004715532,0.000005934819],"category_scores_gemma":[0.0001376961,0.00004819731,0.00003492632,0.001346285,0.00001448916,0.002843036,0.00009932434,0.00002496323,0.0001969352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002426299,"about_ca_system_score_gemma":0.00002628481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000934626,"about_ca_topic_score_gemma":8.891717e-7,"domain_scores_codex":[0.9994488,0.000008360731,0.000167612,0.0001153472,0.0001220693,0.0001378133],"domain_scores_gemma":[0.9994981,0.00006801845,0.00007022222,0.0002906657,0.00005617487,0.00001679356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002084478,0.000005972801,0.0001220411,0.000009502709,0.000003376825,7.38619e-8,0.0000532007,0.0005313189,0.00009074639,0.9067972,0.02110966,0.07127482],"study_design_scores_gemma":[0.0008362008,0.00007470295,0.007636096,0.000003059465,0.000006563677,0.000001258029,0.0002167103,0.6684316,0.01266004,0.239006,0.07084309,0.0002846067],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004697946,0.0000100352,0.9889295,0.002798849,0.0002194229,0.0002345701,0.000002305891,0.00163326,0.001474118],"genre_scores_gemma":[0.916238,0.00009073549,0.07762641,0.0005010086,0.00002225492,0.0002848356,0.0001637218,0.00000573037,0.005067314],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.91154,"threshold_uncertainty_score":0.3421184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02811367513141904,"score_gpt":0.2630281952364658,"score_spread":0.2349145201050468,"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."}}