{"id":"W3034886066","doi":"10.18653/v1/2020.acl-main.707","title":"Iterative Edit-Based Unsupervised Sentence Simplification","year":2020,"lang":"en","type":"article","venue":"","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Waterloo","funders":"Compute Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Computer science; Sentence; Phrase; Artificial intelligence; Simplicity; Natural language processing; Set (abstract data type); Fluency; Word (group theory); Machine learning; Mathematics; Programming language","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":[0.0001222968,0.0001000324,0.00009842966,0.00003041669,0.00009648412,0.0001544941,0.0006024976,0.00004390069,0.00006272602],"category_scores_gemma":[0.000109899,0.00008690063,0.00004698514,0.0004474459,0.00003713165,0.0005053443,0.00005709776,0.00008576327,0.000250587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002595071,"about_ca_system_score_gemma":0.00007910819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000139187,"about_ca_topic_score_gemma":0.000002932726,"domain_scores_codex":[0.9989408,0.00007105617,0.0001989528,0.0004212454,0.0002164007,0.0001515622],"domain_scores_gemma":[0.9991189,0.0001099123,0.00005105812,0.0004445766,0.0001359729,0.0001396069],"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":[0.00006811465,0.0004874137,0.006694167,0.0001331995,0.0000318814,0.00001126887,0.01145383,0.00214002,0.1630706,0.6025634,0.01740251,0.1959436],"study_design_scores_gemma":[0.0003854641,0.0001371391,0.01143833,0.000006772924,0.000004138822,0.000001475443,0.0001329573,0.9174316,0.05407515,0.002194467,0.01392742,0.0002651078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008027425,0.00001091388,0.9518311,0.0378824,0.00008882419,0.000185596,0.000002960778,0.0003539341,0.001616872],"genre_scores_gemma":[0.9594853,0.0000011881,0.03444787,0.005896446,0.0000818295,0.00001945979,0.00001478969,0.00000407953,0.0000490311],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9514579,"threshold_uncertainty_score":0.3543705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03701943317026513,"score_gpt":0.246221930022016,"score_spread":0.2092024968517509,"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."}}