{"id":"W4402715008","doi":"10.18653/v1/2024.sigdial-1.1","title":"Dialogue Discourse Parsing as Generation: A Sequence-to-Sequence LLM-based Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Computer science; Sequence (biology); Parsing; Natural language processing; Artificial intelligence; Programming language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002497894,0.001175179,0.001519869,0.002302241,0.00105333,0.002767561,0.003014743,0.002059162,0.01228801],"category_scores_gemma":[0.007997568,0.0008365585,0.001602466,0.001314556,0.001261183,0.003011353,0.002996415,0.001975189,0.004627376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040258,"about_ca_system_score_gemma":0.001783728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00243882,"about_ca_topic_score_gemma":0.003234618,"domain_scores_codex":[0.9968104,0.001622214,0.0001908479,0.0005673731,0.0006270944,0.0001821077],"domain_scores_gemma":[0.9955058,0.002703422,0.0002062757,0.0007669315,0.0007057594,0.0001118131],"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":[0.000624386,0.00046979,0.001607029,0.0008221797,0.0001710684,0.0008566631,0.001310766,0.07851873,0.03767459,0.1054778,0.02216157,0.7503055],"study_design_scores_gemma":[0.00004150379,0.000112889,0.0003256538,0.00006591773,0.00008739887,0.0002361731,0.0001726054,0.8922328,0.02374075,0.06822491,0.0147102,0.00004911538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002670765,0.0001397879,0.9863088,0.0002590263,0.00006980494,0.0001516992,0.0002243857,0.007594959,0.00258087],"genre_scores_gemma":[0.1423542,0.0001849371,0.8485889,0.000433751,0.0001367752,0.0002811321,0.001132391,0.001677299,0.005210476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01228801,"threshold_uncertainty_score":0.04110748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06300484498857047,"score_gpt":0.3450055187298891,"score_spread":0.2820006737413187,"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."}}