{"id":"W4415724501","doi":"10.1002/sta4.70116","title":"Tensor Train Recurrent Network Language Model Prediction","year":2025,"lang":"en","type":"article","venue":"Stat","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Huawei Technologies","keywords":"Tensor (intrinsic definition); Convolutional neural network; Recurrent neural network; Matrix product state; Computation; Data compression; Reduction (mathematics); Artificial neural network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037757,0.0009740638,0.0006220535,0.0006350729,0.0002597621,0.0009142869,0.0008094944,0.0006094917,0.004287361],"category_scores_gemma":[0.004833551,0.0003143481,0.0006239435,0.0007579889,0.0003638118,0.001438723,0.0005622135,0.001528939,0.001813231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036655,"about_ca_system_score_gemma":0.0008979043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01827527,"about_ca_topic_score_gemma":0.01618575,"domain_scores_codex":[0.9995251,0.0001495067,0.00002931396,0.0001284995,0.00009771348,0.00006990344],"domain_scores_gemma":[0.9978818,0.001173253,0.0001238996,0.0002344513,0.0005338019,0.00005273673],"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":[0.0003231786,0.0001224677,0.002049411,0.0001101587,0.0001061829,0.0001265822,0.00007440029,0.7593279,0.004006248,0.01048442,0.01100165,0.2122674],"study_design_scores_gemma":[0.000001283164,0.000004780732,0.000040947,0.000001455618,0.000001858157,0.000002958112,0.000001866498,0.9985663,0.000355286,0.0008777043,0.000144048,0.000001494288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1417924,0.001508197,0.8389161,0.001572246,0.0004915952,0.000107864,0.002324481,0.007049312,0.006237948],"genre_scores_gemma":[0.8442696,0.0005665085,0.141038,0.0002263517,0.00017779,0.0001145882,0.004084351,0.0003024157,0.009220372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01827527,"threshold_uncertainty_score":0.03633779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.034987884450652,"score_gpt":0.349536399725922,"score_spread":0.3145485152752701,"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."}}