{"id":"W4402716232","doi":"10.1109/cvpr52733.2024.00724","title":"Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions","year":2024,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Class (philosophy); Training (meteorology); Artificial intelligence; Machine learning; Physics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007021963,0.0001494931,0.0001149832,0.0002620361,0.000450015,0.0003875863,0.0005691452,0.00006657474,0.0009527074],"category_scores_gemma":[0.00006024445,0.000120031,0.0001029377,0.0007966802,0.000106171,0.0007588781,0.0002903201,0.0003789365,0.0007956143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002695986,"about_ca_system_score_gemma":0.0001832817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001487378,"about_ca_topic_score_gemma":0.0001401564,"domain_scores_codex":[0.9984365,0.00007113532,0.0003122661,0.000491191,0.0003261345,0.0003628301],"domain_scores_gemma":[0.9990846,0.0004648134,0.0000403629,0.0002717931,0.00005499329,0.00008345615],"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":[0.000004943283,0.00004546818,0.0001476303,0.00001519843,0.00002846017,0.00005023423,0.007970855,0.004764609,0.0006338595,0.9670357,0.005064533,0.01423855],"study_design_scores_gemma":[0.0002768513,0.0000239864,0.004883761,0.00009865162,0.000005374025,0.00007899189,0.000656236,0.8475283,0.00004458202,0.02591886,0.1202556,0.000228777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008208708,0.0005024978,0.8783521,0.00388222,0.001090501,0.0001729764,0.00001260321,0.0004857828,0.1072926],"genre_scores_gemma":[0.982087,0.000004188124,0.005529616,0.0006873976,0.0001713024,0.00005410956,0.00006076118,0.00001507366,0.01139059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9738783,"threshold_uncertainty_score":0.9999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04356958574054237,"score_gpt":0.2866890175643665,"score_spread":0.2431194318238241,"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."}}