{"id":"W7083340380","doi":"","title":"Denoising Neural Reranker for Recommender Systems","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recommender system; Noise reduction; Adversarial system; Noise (video); Minification; Regularization (linguistics); Labrador Retriever","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028048,0.001067454,0.00165876,0.0006961377,0.0004294477,0.0009230979,0.001521183,0.001771993,0.002058189],"category_scores_gemma":[0.008689595,0.0005850554,0.0006581505,0.0007087688,0.00121323,0.001575946,0.001098195,0.002045854,0.001036082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001117105,"about_ca_system_score_gemma":0.0009376929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003900147,"about_ca_topic_score_gemma":0.006022323,"domain_scores_codex":[0.9984056,0.0005344948,0.00008600139,0.000360403,0.0004923696,0.0001210982],"domain_scores_gemma":[0.9968954,0.001862727,0.0002939184,0.0003179538,0.0005277224,0.0001021755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000146911,0.00008300488,0.0007448727,0.0001508019,0.00005649186,0.00009185902,0.00009959625,0.8731735,0.005135871,0.01888274,0.002602339,0.098832],"study_design_scores_gemma":[0.000009030497,0.00003799271,0.00007830483,0.000005093305,0.000006272938,0.00002013408,0.000004756179,0.9938407,0.0007011017,0.004839266,0.0004508662,0.000006434165],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01080863,0.0005034162,0.9863781,0.0002501892,0.00003673094,0.00004290541,0.00005458674,0.0005156002,0.001409808],"genre_scores_gemma":[0.6390136,0.0007588625,0.3458608,0.0005450585,0.0002296121,0.0002443322,0.0004159709,0.0002086861,0.0127231],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003900147,"threshold_uncertainty_score":0.01483339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0467106643572898,"score_gpt":0.271719351145205,"score_spread":0.2250086867879152,"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."}}