{"id":"W4386566497","doi":"10.18653/v1/2023.findings-eacl.194","title":"Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Computer science; Natural language processing; Artificial intelligence; Task (project management); Sentence; Exploit; Language model","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008788412,0.00008555078,0.0001022664,0.00009315421,0.00003097098,0.00007992904,0.0002191157,0.0000558563,0.00001740717],"category_scores_gemma":[0.0000198509,0.00007103113,0.00001660427,0.0001966789,0.00001401111,0.0005646475,0.0001259425,0.0000953081,0.000005367196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001371822,"about_ca_system_score_gemma":0.00001754612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001081929,"about_ca_topic_score_gemma":0.001788932,"domain_scores_codex":[0.9992393,0.00003061209,0.0001326145,0.0003040328,0.0001305308,0.0001628784],"domain_scores_gemma":[0.9995619,0.00007397823,0.00002729824,0.0002854963,0.000009265543,0.00004207944],"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":[0.0000531411,0.0001118236,0.007310424,0.00006429126,0.00005926114,0.0003390796,0.09560706,0.1030935,0.1978112,0.09833695,0.001496124,0.4957172],"study_design_scores_gemma":[0.000263416,0.000008790396,0.01532112,0.00001189352,0.000002078882,0.000001800057,0.0003035411,0.9409586,0.001502553,0.04150782,0.000009888328,0.000108521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7075785,0.00005243704,0.2911119,0.0006416426,0.0001352732,0.00007738705,0.000008575382,0.0001847189,0.0002095664],"genre_scores_gemma":[0.9784617,0.000008758471,0.0209362,0.00006372557,0.00007662885,0.000005409033,0.00002198219,0.000005470442,0.000420081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8378651,"threshold_uncertainty_score":0.2896565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02511427457892696,"score_gpt":0.2887800994238192,"score_spread":0.2636658248448923,"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."}}