{"id":"W4416017620","doi":"10.1145/3746252.3761152","title":"PriviRec: Confidential and Decentralized Graph Filtering for Recommender Systems","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Recommender system; Graph; Filter (signal processing); Aggregate (composite); Overhead (engineering); Collaborative filtering; Adjacency matrix","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001156075,0.000110193,0.0001563241,0.00009502633,0.0001202635,0.0002095682,0.0003342314,0.00004575041,0.000004085132],"category_scores_gemma":[0.00001747057,0.00009833254,0.00005008897,0.0002457145,0.0000282094,0.0003164561,0.0001767722,0.00006155819,0.000001061816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001182278,"about_ca_system_score_gemma":0.00001224512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001368997,"about_ca_topic_score_gemma":0.00001119413,"domain_scores_codex":[0.9991123,0.0000335879,0.0001961765,0.0003227669,0.0000715611,0.0002636208],"domain_scores_gemma":[0.9993934,0.0001908331,0.00004685481,0.0002699385,0.00004172193,0.00005722036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004449963,0.00003750674,0.0009334355,0.0001355453,0.0001025717,0.00000409411,0.0001207324,0.0009852393,0.002753807,0.9075199,0.02198845,0.0653742],"study_design_scores_gemma":[0.005560105,0.000191237,0.001978098,0.0003364653,0.00005500207,0.00005485159,0.0001257493,0.673371,0.009555307,0.1295145,0.1782328,0.001024897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002972887,0.0004684561,0.9930774,0.0007620721,0.001281467,0.0004186492,0.000001390835,0.0001958562,0.0008218204],"genre_scores_gemma":[0.8300961,0.0003982981,0.1654459,0.001561068,0.00006646548,0.0001829473,0.000004871522,0.00001611608,0.0022282],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8276315,"threshold_uncertainty_score":0.4009885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187131860750584,"score_gpt":0.2720351757435328,"score_spread":0.2601638571360269,"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."}}