{"id":"W4413147183","doi":"10.1109/cvpr52734.2025.01412","title":"DEIM: DETR with Improved Matching for Fast Convergence","year":2025,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":162,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"Hefei Normal University","keywords":"Convergence (economics); Matching (statistics); Computer science; Mathematics; Statistics","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":[0.00004247953,0.00005514574,0.00005647393,0.00002012104,0.0001187609,0.00007812685,0.0003693267,0.00001501262,0.000005692268],"category_scores_gemma":[0.000001801405,0.00003923779,0.00001999801,0.0002442545,0.00001338814,0.0001292896,0.00007852264,0.0000364442,0.000005452763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007093614,"about_ca_system_score_gemma":0.00003093646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002658432,"about_ca_topic_score_gemma":0.00005296229,"domain_scores_codex":[0.9995517,0.000003769451,0.0000772978,0.0001966748,0.00003805091,0.0001325703],"domain_scores_gemma":[0.9996049,0.00006070289,0.00002165249,0.0002441641,0.0000398112,0.00002872425],"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":[0.00000573239,0.00002609543,0.0002606492,0.00001459703,0.0000126316,4.449494e-7,0.00005220539,0.0003228461,0.0064673,0.9265116,0.004259477,0.06206645],"study_design_scores_gemma":[0.0006667188,0.0001104358,0.00168778,0.00004014896,0.0000130549,0.000005589713,0.00006779956,0.8836173,0.02936918,0.0540258,0.0300822,0.0003139128],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005835317,0.00001606914,0.9888211,0.002261254,0.00009138028,0.0002209775,7.539189e-7,0.0001074392,0.002645724],"genre_scores_gemma":[0.8148328,0.000003700137,0.1798879,0.001302319,0.00002161201,0.0001015931,8.486048e-7,0.000002891085,0.003846321],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8832945,"threshold_uncertainty_score":0.1600071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007133822222443246,"score_gpt":0.2442538496037568,"score_spread":0.2371200273813136,"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."}}