{"id":"W4401857430","doi":"10.1145/3637528.3671474","title":"A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)","year":2024,"lang":"en","type":"review","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Recommender system; Computer science; Generative grammar; Generative model; Artificial intelligence; Key (lock); Multidisciplinary approach; Machine learning; Data science; Information retrieval","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":[0.002703366,0.001371888,0.001607609,0.002405819,0.0004529054,0.001600542,0.001921948,0.001478648,0.005392595],"category_scores_gemma":[0.007163253,0.00101443,0.001413578,0.005387709,0.0004867467,0.003069227,0.001103106,0.001672757,0.005250554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001013702,"about_ca_system_score_gemma":0.001952738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005514679,"about_ca_topic_score_gemma":0.005699286,"domain_scores_codex":[0.9990108,0.0003147034,0.0001062881,0.0002210023,0.0002944803,0.00005273129],"domain_scores_gemma":[0.9953344,0.003331728,0.0001443173,0.0003212806,0.0007821962,0.0000860907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006168792,0.0001058872,0.001296214,0.009642384,0.0003309304,0.00008826811,0.0001452098,0.006710983,0.0007202828,0.02123026,0.04686753,0.9128004],"study_design_scores_gemma":[0.00003521033,0.000331483,0.002452581,0.00474759,0.0005646694,0.001125932,0.0001712429,0.01839652,0.001157233,0.0254325,0.9454442,0.0001408337],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009591589,0.9656479,0.02606608,0.001538524,0.0004679279,0.00004321058,0.0002791735,0.0002312319,0.004766715],"genre_scores_gemma":[0.01100471,0.9608331,0.02271017,0.0009451344,0.001239593,0.00006912638,0.0006757671,0.00007534424,0.002447045],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005514679,"threshold_uncertainty_score":0.01804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3534450477250533,"score_gpt":0.4060754439442824,"score_spread":0.05263039621922905,"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."}}