{"id":"W4400649796","doi":"10.1109/iv55156.2024.10588635","title":"TrACT: A Training Dynamics Aware Contrastive Learning Framework for Long-Tail Trajectory Prediction","year":2024,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); University of Toronto","funders":"","keywords":"Trajectory; Computer science; Training (meteorology); Dynamics (music); Artificial intelligence; Machine learning; Psychology","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":[0.0007496486,0.001421946,0.0009591528,0.0008116261,0.0005523002,0.0008814231,0.003048625,0.001511316,0.002387656],"category_scores_gemma":[0.003348359,0.0006538221,0.0009149858,0.0007398585,0.0007320435,0.001706995,0.001631074,0.002824024,0.001123293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001151421,"about_ca_system_score_gemma":0.001285296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01311618,"about_ca_topic_score_gemma":0.01854363,"domain_scores_codex":[0.9995818,0.00007183749,0.000015818,0.0001837332,0.00008539166,0.00006139701],"domain_scores_gemma":[0.9992719,0.0002975807,0.00007985465,0.000123269,0.0001508029,0.00007663501],"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":[0.0003918271,0.0003240438,0.003772315,0.0000927936,0.0001108231,0.0001935307,0.0001160444,0.762929,0.006981077,0.00650524,0.007221648,0.2113616],"study_design_scores_gemma":[0.000006241773,0.00002368727,0.00009255642,0.000003393774,0.000003519697,0.000009301855,0.000003741713,0.997848,0.0004645812,0.001256199,0.0002854293,0.000003239901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03538215,0.0004078761,0.9564244,0.0002737225,0.00009597593,0.0001009254,0.0007024552,0.00502811,0.001584373],"genre_scores_gemma":[0.6680217,0.0002518979,0.3223758,0.0003740379,0.0001184352,0.0002988214,0.003544805,0.0005294749,0.004485124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01311618,"threshold_uncertainty_score":0.02607965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01429244463012114,"score_gpt":0.2433042015974967,"score_spread":0.2290117569673756,"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."}}