{"id":"W4417509034","doi":"10.1109/icsit65336.2025.11294625","title":"Bias Mitigation in Generative Chatbots Through Adversarial Debiasing","year":2025,"lang":"en","type":"article","venue":"","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Debiasing; Adversarial system; Generative grammar; Generator (circuit theory); Chatbot; Semantics (computer science); Scalability; Presentation (obstetrics)","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":[0.0001052774,0.00008048617,0.00008862144,0.0001130406,0.00008811153,0.0001240467,0.000351865,0.00004988739,0.00003774984],"category_scores_gemma":[0.000049943,0.00007751515,0.00003330872,0.0006142175,0.00001773295,0.001142423,0.0001589312,0.0001120023,0.00005887579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001222588,"about_ca_system_score_gemma":0.0000961015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004908378,"about_ca_topic_score_gemma":0.001044331,"domain_scores_codex":[0.9992145,0.00007370357,0.0001961338,0.0002549473,0.0001126779,0.0001480881],"domain_scores_gemma":[0.9994277,0.000169924,0.00004347175,0.0002712065,0.00007041111,0.00001731435],"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":[0.00001324855,0.0001437131,0.00353865,0.0000149493,0.00003985495,0.00001736011,0.0100591,0.003453206,0.003908147,0.9412858,0.005343996,0.03218192],"study_design_scores_gemma":[0.001561068,0.00006991193,0.01279313,0.0002643102,0.00001440515,0.00002851394,0.001824378,0.7077875,0.1153994,0.1464852,0.013241,0.0005311579],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05978514,0.00002507408,0.889084,0.007678234,0.001348109,0.0001329244,4.970638e-7,0.0001214848,0.04182453],"genre_scores_gemma":[0.8363457,0.000005159094,0.1590576,0.003063035,0.0000793794,0.00001906739,0.000002725635,0.000003600604,0.001423765],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7948006,"threshold_uncertainty_score":0.3160976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03447970287039379,"score_gpt":0.3151587259728274,"score_spread":0.2806790231024336,"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."}}