{"id":"W4402702960","doi":"10.1109/cvpr52733.2024.00796","title":"Scaling Up Video Summarization Pretraining with Large Language Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Automatic summarization; Computer science; Scaling; Natural language processing; Artificial intelligence; Language model; Mathematics","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":[0.0003743585,0.000103601,0.0001117519,0.0001663355,0.000105632,0.0006193006,0.0002613383,0.00004717051,0.00005051298],"category_scores_gemma":[0.00002091877,0.00007537963,0.00004973064,0.0008454349,0.000009689849,0.001297881,0.00008652458,0.00008937703,0.0000277662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002622905,"about_ca_system_score_gemma":0.00005818048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003610158,"about_ca_topic_score_gemma":0.0000568785,"domain_scores_codex":[0.9989403,0.00003878845,0.0001722634,0.0003619645,0.0002788202,0.0002078913],"domain_scores_gemma":[0.9995109,0.00005944452,0.00002709347,0.0002899422,0.00005734709,0.00005531151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003706915,0.00002389476,0.0004388663,0.00004516077,0.00007645227,0.00003404791,0.00872122,0.02208455,0.0006349772,0.8618907,0.0007019389,0.1053445],"study_design_scores_gemma":[0.0001001151,0.00001501296,0.0000503615,0.00005757806,0.00001522865,0.000003732979,0.0002133376,0.9962102,0.0005641384,0.002057909,0.0005890346,0.0001233964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003819761,0.0002874634,0.9837134,0.0003461143,0.0001552684,0.00007104316,0.000001948907,0.000461385,0.01114361],"genre_scores_gemma":[0.9709181,0.00001433348,0.02630181,0.0002516349,0.00005809083,0.000006445074,0.00003037438,0.00001236,0.002406872],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9741256,"threshold_uncertainty_score":0.597193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230332878457298,"score_gpt":0.2431677259108387,"score_spread":0.2308643971262657,"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."}}