{"id":"W4407130178","doi":"10.1109/smap63474.2024.00028","title":"MMREC: LLM Based Multi-Modal Recommender System","year":2024,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Recommender system; Modal; Computer 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":[0.001210941,0.0007175978,0.001360159,0.0008817145,0.0008054517,0.001015054,0.002042069,0.001557374,0.004633589],"category_scores_gemma":[0.002933247,0.0003798319,0.001002304,0.0009420256,0.0003943835,0.001678701,0.001325966,0.001688868,0.002723669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000893346,"about_ca_system_score_gemma":0.0009911305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0172377,"about_ca_topic_score_gemma":0.03477209,"domain_scores_codex":[0.9989859,0.0003105027,0.00005608881,0.0002845604,0.0002695289,0.00009339034],"domain_scores_gemma":[0.9989742,0.0003550599,0.00006982054,0.0002203721,0.000318212,0.00006234856],"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":[0.0008692931,0.0007389924,0.006197855,0.0004935293,0.0005058973,0.0006012947,0.000360003,0.192564,0.02735217,0.0173656,0.05777514,0.6951763],"study_design_scores_gemma":[0.00002976403,0.00009459764,0.0005498176,0.00001360318,0.00003854474,0.0001502324,0.00002820911,0.9891217,0.001971296,0.003482638,0.004484475,0.0000350385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02559409,0.001601707,0.9577745,0.00111277,0.0002592112,0.0001727229,0.001042097,0.006898843,0.005544037],"genre_scores_gemma":[0.5555111,0.0009101327,0.4204658,0.001529987,0.0002539421,0.000333778,0.002558668,0.0002288082,0.01820771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0172377,"threshold_uncertainty_score":0.0342747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02116551148508732,"score_gpt":0.290798358730528,"score_spread":0.2696328472454407,"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."}}