{"id":"W4405868575","doi":"10.1145/3696409.3700188","title":"LMoW: A Latent Random Variable Model for Unconditional Human Motion Generation","year":2024,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Latent variable; Variable (mathematics); Computer science; Random variable; Artificial intelligence; Statistics; Mathematics","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":[0.001679479,0.00113881,0.001496705,0.000892878,0.0005286325,0.0009674712,0.003477157,0.002219961,0.00987342],"category_scores_gemma":[0.004351192,0.001019947,0.001945718,0.0009845425,0.0006777107,0.001565374,0.002215039,0.003233024,0.004634841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006771084,"about_ca_system_score_gemma":0.001188337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007897594,"about_ca_topic_score_gemma":0.01262072,"domain_scores_codex":[0.9992893,0.0002550445,0.00002826964,0.0002294597,0.0001186549,0.00007933674],"domain_scores_gemma":[0.9989414,0.0006275905,0.00005823122,0.0001823599,0.00012045,0.00007004433],"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":[0.001076168,0.0002956653,0.001980984,0.0003002088,0.0003517857,0.0002389918,0.0001814683,0.3810368,0.008221327,0.04649631,0.03493098,0.5248892],"study_design_scores_gemma":[0.00002383602,0.00002714591,0.0001442024,0.000009692087,0.00001123333,0.00002223506,0.000005267421,0.9864477,0.000803282,0.01072422,0.001768654,0.00001252094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002168485,0.0001366796,0.9925959,0.0001013112,0.00005328006,0.00004576261,0.0007906251,0.00389032,0.0002176948],"genre_scores_gemma":[0.1842819,0.0004953894,0.7900444,0.0005774238,0.0002634518,0.00102433,0.01084473,0.002472532,0.009995885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00987342,"threshold_uncertainty_score":0.03302985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05606831932522927,"score_gpt":0.2828491962567803,"score_spread":0.226780876931551,"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."}}