{"id":"W4402753812","doi":"10.1109/cvpr52733.2024.01268","title":"Posterior Distillation Sampling","year":2024,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Institute for Information and Communications Technology Promotion; Samsung; Neurosciences Research Foundation","keywords":"Sampling (signal processing); Computer science; Distillation; Chromatography; Computer vision; Chemistry","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":[0.001426602,0.001220293,0.001004405,0.0007940226,0.0005388216,0.001679655,0.001713722,0.001219185,0.008533125],"category_scores_gemma":[0.005757025,0.0006798138,0.001007228,0.0007540711,0.001207619,0.002121237,0.002577949,0.002305303,0.001933767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008711834,"about_ca_system_score_gemma":0.001195824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002024732,"about_ca_topic_score_gemma":0.002874987,"domain_scores_codex":[0.9990238,0.0002787934,0.00003753849,0.0002361974,0.0003355914,0.00008804639],"domain_scores_gemma":[0.9984617,0.000860937,0.00009943508,0.0002900471,0.0001983653,0.00008947846],"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":[0.0002875646,0.0001255561,0.001350738,0.0003406044,0.0001009215,0.0002913362,0.0002426306,0.5015022,0.01909916,0.1789655,0.01197106,0.2857227],"study_design_scores_gemma":[0.00002022505,0.00003525308,0.0001104288,0.000020035,0.00001066738,0.000093079,0.00001465571,0.9483639,0.00437984,0.03939259,0.007537832,0.00002141184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002751449,0.0001630916,0.9938694,0.0001302249,0.00004589077,0.00003479472,0.00008461817,0.0005377891,0.002382603],"genre_scores_gemma":[0.2025809,0.0005536544,0.7817664,0.0005150803,0.0001780864,0.0003400464,0.0007791116,0.001548366,0.01173848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008533125,"threshold_uncertainty_score":0.02854615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328596196149229,"score_gpt":0.3042459701831524,"score_spread":0.2809600082216601,"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."}}