{"id":"W6901609953","doi":"10.60692/fm597-ea287","title":"An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Models","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Debiasing; Counterfactual thinking; Language model; Empirical research; Work (physics); Natural language understanding; Exploit; Cognitive bias","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":[0.01723992,0.00215835,0.001120021,0.002026672,0.000850082,0.001482519,0.002077036,0.001514192,0.001483708],"category_scores_gemma":[0.07119617,0.0007053333,0.001346796,0.001631581,0.001246338,0.003971881,0.002081913,0.003284953,0.001392777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001265592,"about_ca_system_score_gemma":0.001522235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005360618,"about_ca_topic_score_gemma":0.007909249,"domain_scores_codex":[0.9890616,0.006279328,0.0009644416,0.001701131,0.001686836,0.0003065865],"domain_scores_gemma":[0.9380484,0.04837565,0.001896051,0.007781563,0.003367352,0.0005309698],"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":[0.00102214,0.0004551395,0.0383324,0.002788338,0.001187413,0.0001455042,0.001076782,0.08768324,0.01189786,0.002812446,0.01383184,0.8387668],"study_design_scores_gemma":[0.0002705104,0.002638299,0.03934424,0.001693295,0.0009542181,0.001062648,0.001569184,0.8260099,0.08001865,0.00962093,0.03655287,0.0002653027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6076725,0.0563698,0.295606,0.003765657,0.0006384123,0.0007045708,0.0032514,0.02035321,0.01163836],"genre_scores_gemma":[0.7779422,0.008596146,0.20053,0.0008294429,0.0002210003,0.0003872617,0.007508436,0.001252334,0.002733163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01723992,"threshold_uncertainty_score":0.09117454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05684934228093712,"score_gpt":0.2904300126992049,"score_spread":0.2335806704182678,"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."}}