{"id":"W4401863720","doi":"10.1145/3637528.3671733","title":"Probabilistic Attention for Sequential Recommendation","year":2024,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Google (Canada)","funders":"","keywords":"Probabilistic logic; Computer science; Artificial intelligence","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":[0.002067273,0.001064385,0.001768205,0.00153108,0.0007609813,0.001265682,0.0026362,0.00142438,0.004922775],"category_scores_gemma":[0.008658622,0.0008053677,0.001284656,0.002182923,0.0009194608,0.002840355,0.001637867,0.002108627,0.001103833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002280224,"about_ca_system_score_gemma":0.001550181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02153653,"about_ca_topic_score_gemma":0.01849194,"domain_scores_codex":[0.9979461,0.0004821659,0.00009956501,0.0006029136,0.0006576081,0.0002116421],"domain_scores_gemma":[0.9958323,0.002707083,0.0002923259,0.0005395151,0.0004748439,0.0001540116],"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":[0.0003236759,0.0001812769,0.002941212,0.0004099293,0.0002379149,0.0001949828,0.0002886685,0.6096026,0.005005898,0.09803095,0.007828042,0.2749548],"study_design_scores_gemma":[0.000009888532,0.00003060497,0.0003437412,0.000007032418,0.00002285393,0.00003607013,0.000006751752,0.9751604,0.0003696121,0.02307151,0.0009290409,0.00001248588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01886236,0.0014506,0.9740339,0.0004014322,0.00008626243,0.00007318331,0.0002256009,0.001117611,0.003748951],"genre_scores_gemma":[0.8201106,0.001877579,0.1654267,0.0004394219,0.0003819246,0.0002449827,0.0006050902,0.0001665804,0.01074716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02153653,"threshold_uncertainty_score":0.04282236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04397014614760297,"score_gpt":0.3128859607941188,"score_spread":0.2689158146465158,"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."}}