{"id":"W4410636510","doi":"10.1145/3701716.3717531","title":"Beyond Retrieval: Generating Narratives in Conversational Recommender Systems","year":2025,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Recommender system; Computer science; Narrative; Information retrieval; Natural language processing; World Wide Web; Artificial intelligence; Human–computer interaction; Linguistics","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":[0.007106256,0.001300959,0.0008998784,0.001493454,0.001746106,0.003889413,0.002156764,0.002259494,0.004241102],"category_scores_gemma":[0.04155974,0.0009053067,0.001192048,0.00122384,0.001149835,0.008032557,0.003793746,0.002515333,0.002727368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001119424,"about_ca_system_score_gemma":0.001580319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004917223,"about_ca_topic_score_gemma":0.006469396,"domain_scores_codex":[0.9941118,0.0040424,0.0002642775,0.0008366351,0.0005564235,0.0001884115],"domain_scores_gemma":[0.9748045,0.02016066,0.001024103,0.002120822,0.001334803,0.0005550339],"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":[0.001531912,0.0007415172,0.02108047,0.002038256,0.0004647555,0.001726136,0.02939796,0.1249807,0.01558887,0.1608568,0.03959854,0.6019942],"study_design_scores_gemma":[0.0001252777,0.0001964773,0.001348083,0.0002451922,0.000145691,0.0004782198,0.003382424,0.8052732,0.00961298,0.1368915,0.04217517,0.0001257134],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05812885,0.002400253,0.9226897,0.004512872,0.0002404943,0.0006598358,0.001911873,0.002352581,0.007103432],"genre_scores_gemma":[0.4711159,0.001184824,0.5156565,0.0006855534,0.0003037186,0.0005874699,0.004011997,0.0004733168,0.00598072],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007106256,"threshold_uncertainty_score":0.03758192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02869610046458668,"score_gpt":0.2743105291464985,"score_spread":0.2456144286819118,"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."}}