{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008313953,0.0002136514,0.0003241174,0.0001330339,0.0002949062,0.0004229252,0.0004373943,0.00006883765,0.000007749975],"category_scores_gemma":[0.0000506399,0.0001708265,0.0001143279,0.0003607117,0.00003138928,0.0002712738,0.0001756319,0.0001364769,0.000007542006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001179072,"about_ca_system_score_gemma":0.0001348114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003961294,"about_ca_topic_score_gemma":0.0001397768,"domain_scores_codex":[0.9981859,0.0002939962,0.0003636192,0.000564235,0.0002596036,0.0003326974],"domain_scores_gemma":[0.9985316,0.0005483641,0.00004451897,0.0005860586,0.0002010679,0.00008840768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005634971,0.009520271,0.005359719,0.0005042222,0.003480432,0.009189405,0.07583784,0.06241703,0.0005783642,0.2618527,0.2168245,0.353872],"study_design_scores_gemma":[0.0012016,0.0003979212,0.00008559463,0.00003477022,0.00003789413,0.00005342102,0.007277227,0.9888676,0.000163049,0.00005024979,0.001626849,0.0002038066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007443967,0.0001630128,0.9875756,0.0006910964,0.0009721469,0.001785114,0.000004825556,0.0001679109,0.001196349],"genre_scores_gemma":[0.9106972,0.000002957586,0.07951923,0.002001064,0.0002301153,0.0008460062,0.000007176338,0.00001190403,0.006684361],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9264506,"threshold_uncertainty_score":0.6966105,"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."}}