{"id":"W4415535455","doi":"10.1145/3746027.3758147","title":"Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds","year":2025,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; McGill University","funders":"","keywords":"Personalization; Scalability; Adaptability; Generative grammar; Resource (disambiguation); Reinforcement learning; Generative model","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":[0.001206472,0.0005076025,0.00036125,0.0005487478,0.0007641168,0.0009315237,0.0007998096,0.00119901,0.00161463],"category_scores_gemma":[0.003589908,0.0001725301,0.0003705847,0.0007044526,0.0008189771,0.001300871,0.0008293019,0.0008536503,0.0001628455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360817,"about_ca_system_score_gemma":0.000506583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00552863,"about_ca_topic_score_gemma":0.006559851,"domain_scores_codex":[0.9994936,0.0002674556,0.00001548092,0.00006119473,0.0001013324,0.00006099406],"domain_scores_gemma":[0.9979883,0.001528177,0.00009314896,0.0001240933,0.0001556688,0.0001106315],"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":[0.0002046094,0.0002640479,0.00545321,0.0001146178,0.00003964307,0.001325436,0.0004228784,0.8682121,0.005364662,0.03073512,0.001927436,0.08593632],"study_design_scores_gemma":[0.00001191476,0.00007057132,0.0006367569,0.00001053621,0.000009706892,0.0001816534,0.0001322465,0.9840391,0.00353902,0.008810738,0.002544595,0.00001307965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4344268,0.0005867146,0.5520494,0.0007465334,0.00006172325,0.000359081,0.0001949181,0.0005990001,0.01097579],"genre_scores_gemma":[0.9087481,0.0002867204,0.08779422,0.00007479848,0.000021542,0.00008921183,0.0001078558,0.0000492871,0.002828213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00552863,"threshold_uncertainty_score":0.01099288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0510384200643972,"score_gpt":0.3623712983120752,"score_spread":0.311332878247678,"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."}}