{"id":"W4400647277","doi":"10.1109/iv55156.2024.10588698","title":"Vectorized Representation Dreamer (VRD): Dreaming-Assisted Multi-Agent Motion Forecasting","year":2024,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Representation (politics); Motion (physics); Artificial intelligence; Computer vision; Computer graphics (images); Law; Political science","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":[0.0007346051,0.001134597,0.0009385644,0.0007104882,0.0003094982,0.0007113669,0.002460452,0.0009556363,0.001669434],"category_scores_gemma":[0.002231214,0.0005390029,0.0007224036,0.0007303523,0.0003443397,0.001465442,0.001107901,0.00178322,0.0007944926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000567277,"about_ca_system_score_gemma":0.0008031781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01275111,"about_ca_topic_score_gemma":0.01744707,"domain_scores_codex":[0.9997512,0.0000558049,0.00001635361,0.00009915149,0.0000477428,0.00002981793],"domain_scores_gemma":[0.9994486,0.0002132036,0.00004955595,0.0001606804,0.00008977352,0.00003825642],"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":[0.000238578,0.00017096,0.00382142,0.0001972862,0.0001262861,0.0001637097,0.0001374583,0.7066073,0.002743538,0.005089971,0.02594299,0.2547604],"study_design_scores_gemma":[0.000008911503,0.00001783876,0.0001469196,0.000005744706,0.000004447289,0.00001845975,0.00001043378,0.9963147,0.0005082742,0.001730951,0.001227105,0.000006131501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04750591,0.001640838,0.9256764,0.0009626767,0.0003081126,0.0001424203,0.004247079,0.01674494,0.002771564],"genre_scores_gemma":[0.5389407,0.0007102566,0.4414597,0.0003925944,0.0001001096,0.0002044586,0.01367287,0.0003531441,0.004166133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01275111,"threshold_uncertainty_score":0.02535379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07113323685812299,"score_gpt":0.2888729152148758,"score_spread":0.2177396783567528,"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."}}