{"id":"W4413157189","doi":"10.1109/cvpr52734.2025.02399","title":"NoT: Federated Unlearning via Weight Negation","year":2025,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Negation; Computer science; Programming language; Natural language processing; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000127453,0.00006138698,0.00006244999,0.0001086032,0.000200441,0.0002235155,0.0002922204,0.00003818853,0.00006069513],"category_scores_gemma":[0.00001992317,0.00005428065,0.00003311606,0.000705054,0.00001508167,0.0004474444,0.000143711,0.00009051984,0.00005410352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009704737,"about_ca_system_score_gemma":0.00002905719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006944739,"about_ca_topic_score_gemma":0.00003530014,"domain_scores_codex":[0.9994216,0.00003590839,0.0001082059,0.0002160617,0.00009553562,0.0001226883],"domain_scores_gemma":[0.999608,0.00005354244,0.0000239564,0.0002368331,0.00004746822,0.00003020066],"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":[0.00000458022,0.00002881178,0.001114111,0.000006550453,0.00001085303,0.000002331001,0.0001126283,0.0000128479,0.001549532,0.9254304,0.004949068,0.06677829],"study_design_scores_gemma":[0.001021638,0.00007276204,0.03987442,0.00005045975,0.00001401389,0.000006995019,0.00005518799,0.5778012,0.06221459,0.1204569,0.1979417,0.0004902146],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005209095,0.00003044154,0.9658132,0.001472513,0.0002679284,0.00005230067,6.591632e-7,0.0002509012,0.02690299],"genre_scores_gemma":[0.960172,0.000007688789,0.03820477,0.001323925,0.00002095898,0.000003871166,0.00001049957,0.000001689459,0.000254574],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9549629,"threshold_uncertainty_score":0.2213501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006909984337206653,"score_gpt":0.2329608501765085,"score_spread":0.2260508658393018,"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."}}