{"id":"W4413147453","doi":"10.1109/cvpr52734.2025.02128","title":"Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction","year":2025,"lang":"en","type":"article","venue":"","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Samsung; Arm","keywords":"Computer science; Computer vision; Lexical analysis; Computer graphics (images); Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000168814,0.0001069999,0.0001042989,0.000245132,0.00008767611,0.000181568,0.0002529322,0.00006111999,0.000019296],"category_scores_gemma":[0.00009053054,0.0001009277,0.00004677231,0.001039625,0.00004658319,0.0002540441,0.00008221411,0.00007344007,0.0000811167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250663,"about_ca_system_score_gemma":0.00008018201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006196079,"about_ca_topic_score_gemma":0.00004671174,"domain_scores_codex":[0.9990354,0.00003383751,0.0002177576,0.000332751,0.0001958386,0.0001844284],"domain_scores_gemma":[0.999288,0.00007282705,0.00006182164,0.00035929,0.0001653045,0.00005280592],"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":[0.000009177702,0.00005248796,0.002418778,0.00001889223,0.000009021864,0.000003497831,0.0000266279,0.009374089,0.0004534428,0.008603856,0.0005169246,0.9785132],"study_design_scores_gemma":[0.0003868142,0.00005327608,0.003505989,0.0000462005,0.000005829156,0.00001316718,0.000009797536,0.9427112,0.04993869,0.002788408,0.0004054498,0.000135187],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09304154,0.00001082131,0.8884956,0.0007428785,0.00270196,0.0001811966,3.806335e-7,0.0004072862,0.0144184],"genre_scores_gemma":[0.9847023,4.117966e-7,0.01419311,0.0003255621,0.00002472567,0.00001738395,0.000002978538,0.000004901214,0.0007286484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.978378,"threshold_uncertainty_score":0.411571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004106213569763425,"score_gpt":0.2026655960940346,"score_spread":0.1985593825242712,"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."}}