{"id":"W4389520668","doi":"10.18653/v1/2023.emnlp-main.404","title":"Efficient Classification of Long Documents via State-Space Models","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Computation; Robustness (evolution); Artificial intelligence; Machine learning; Transformer; Binary classification; Extrapolation; Binary number; Data mining; Pattern recognition (psychology); Algorithm; Support vector machine; Mathematics","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":[0.0009780504,0.0008054267,0.0009607857,0.001000528,0.0003607836,0.001400389,0.001157213,0.001069036,0.002322664],"category_scores_gemma":[0.003344418,0.0003764559,0.00108063,0.001158124,0.0004120574,0.002704851,0.0007829533,0.001932841,0.001539014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008724582,"about_ca_system_score_gemma":0.0009854378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005212446,"about_ca_topic_score_gemma":0.006889629,"domain_scores_codex":[0.9995692,0.000120647,0.0000308808,0.0001460447,0.00007872254,0.00005447447],"domain_scores_gemma":[0.9981382,0.001255267,0.0001296658,0.0002034291,0.0002262723,0.00004707008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003335788,0.0002025718,0.002090768,0.0001722328,0.0001083114,0.0001105477,0.0001823721,0.5311338,0.006731405,0.01791316,0.00654565,0.4344757],"study_design_scores_gemma":[0.000003188048,0.00001008613,0.00007707164,0.000002898842,0.00000471264,0.000007655113,0.000006236617,0.9942492,0.0006534086,0.004762463,0.0002201034,0.000002975367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04573365,0.0007676228,0.9474617,0.0005000937,0.0000750508,0.00005996665,0.0004219406,0.003494889,0.001485088],"genre_scores_gemma":[0.8039085,0.0007591208,0.1847535,0.0003035406,0.0001859322,0.000208794,0.002318703,0.0002639869,0.007297887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005212446,"threshold_uncertainty_score":0.01036423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04326352365658225,"score_gpt":0.2815403646310278,"score_spread":0.2382768409744455,"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."}}