{"id":"W4281390966","doi":"10.1145/3488932.3517402","title":"InfoCensor","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mutual information; Computer science; Artificial intelligence; Machine learning; Inference; Interaction information; Deep learning; Adversary; Adversarial system; Bounded function; Softmax function; Mathematics; Computer security","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":[0.00291277,0.001671325,0.001463306,0.002395458,0.001346326,0.00491054,0.004323754,0.002673254,0.2828968],"category_scores_gemma":[0.01800187,0.0009092712,0.001815233,0.002209735,0.001379981,0.006735273,0.005987963,0.004087173,0.1743402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358857,"about_ca_system_score_gemma":0.003303956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002193314,"about_ca_topic_score_gemma":0.003134946,"domain_scores_codex":[0.997393,0.0004814476,0.0001657317,0.0004653733,0.001150778,0.000343568],"domain_scores_gemma":[0.993298,0.001236973,0.0003401524,0.003690245,0.0009774567,0.0004571153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005273387,0.0001052108,0.0007883128,0.0006404218,0.0001117065,0.0002823616,0.0001031493,0.003325884,0.002055309,0.04890063,0.6979102,0.2452495],"study_design_scores_gemma":[0.0001454189,0.00009381088,0.0004351697,0.0002420794,0.00005082642,0.0004581211,0.00004814688,0.03020524,0.01093239,0.06763923,0.8896725,0.0000771922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.006071171,0.004790181,0.3351064,0.0130893,0.007793467,0.0009684626,0.06597333,0.2251618,0.3410458],"genre_scores_gemma":[0.1731233,0.008919221,0.1441618,0.01031624,0.004091891,0.002142585,0.1629513,0.04250858,0.4517851],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2828968,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02784295292011382,"score_gpt":0.2723720666151164,"score_spread":0.2445291136950026,"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."}}