{"id":"W7160169153","doi":"10.1109/iccv51701.2025.00048","title":"Multimodal Large Language Model-Guided ISP Hyperparameter Optimization with Dynamic Preference Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Preference; Hyperparameter; Preference learning; Statistical learning; Deep learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001705081,0.001833928,0.001875245,0.001142638,0.0008955601,0.001683522,0.002137998,0.002619603,0.009017782],"category_scores_gemma":[0.00810367,0.0009360469,0.001298409,0.001274646,0.001195934,0.002917414,0.002762042,0.002648913,0.001711002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166514,"about_ca_system_score_gemma":0.002027201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006475369,"about_ca_topic_score_gemma":0.01059122,"domain_scores_codex":[0.9991391,0.0003753818,0.00003865293,0.0001632231,0.0001413427,0.0001422112],"domain_scores_gemma":[0.9979479,0.001301166,0.00009566994,0.0002104017,0.0003162326,0.0001286921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003046684,0.0001829775,0.0005916643,0.0001251884,0.00006948526,0.0001825907,0.000149305,0.861005,0.002922771,0.01425644,0.008722497,0.1114874],"study_design_scores_gemma":[0.00001151892,0.0000131937,0.00002249462,0.000004020597,0.00000552625,0.00001055623,0.00001486319,0.9946886,0.0002665755,0.004785744,0.0001725582,0.00000442483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02081436,0.0003028851,0.9724152,0.0004967749,0.00009268457,0.00006809195,0.0001291717,0.001756688,0.003924091],"genre_scores_gemma":[0.6829855,0.0001952438,0.3055877,0.0007415324,0.0001248549,0.0003801551,0.0005401306,0.001284096,0.008160627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009017782,"threshold_uncertainty_score":0.03016752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01746560321178599,"score_gpt":0.2840759164750276,"score_spread":0.2666103132632416,"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."}}