{"id":"W6910455246","doi":"10.48448/hdb0-6t03","title":"Turn the Combination Lock: Learnable Textual Backdoor Attacks via Word Substitution","year":2021,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Backdoor; Word (group theory); Invisibility; Code (set theory); Substitution (logic); ALARM","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":[0.001369235,0.001126989,0.0007372954,0.0007101697,0.0004923409,0.001686031,0.001455226,0.001538139,0.009722685],"category_scores_gemma":[0.01108841,0.0004525664,0.0009164285,0.0004671599,0.001913081,0.004411271,0.003700436,0.002331147,0.005452638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005285885,"about_ca_system_score_gemma":0.0007894544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009753773,"about_ca_topic_score_gemma":0.001449398,"domain_scores_codex":[0.9979331,0.0007276743,0.0001289479,0.0004810897,0.0005551969,0.0001739283],"domain_scores_gemma":[0.9950646,0.002199068,0.0003868519,0.001922938,0.0002775998,0.0001490587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003071128,0.0007391369,0.01247046,0.0009241609,0.000563606,0.002669081,0.001228897,0.1279327,0.09965492,0.08555417,0.05952432,0.6056674],"study_design_scores_gemma":[0.0001565319,0.0004647197,0.001107755,0.0001082822,0.0001249875,0.00104587,0.000200492,0.7821457,0.07636261,0.1112623,0.02692086,0.00009978763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1784478,0.001332825,0.7484888,0.002566064,0.0006073749,0.0002562673,0.002123821,0.04349333,0.02268376],"genre_scores_gemma":[0.872147,0.0003780868,0.1093015,0.001001903,0.0001061536,0.0001599923,0.002078508,0.002326447,0.01250035],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009722685,"threshold_uncertainty_score":0.0325256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641973718675312,"score_gpt":0.2982051489102547,"score_spread":0.2717854117235016,"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."}}