{"id":"W4409506451","doi":"10.1007/978-3-031-85356-2_5","title":"A High Parallelization Method for Automated Formal Verification of Deep Neural Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Artificial neural network; Deep neural networks; Formal methods; Parallel computing; Formal verification; Artificial intelligence; Programming language","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00125645,0.0004027864,0.00056474,0.0006922553,0.0002717216,0.0002136514,0.002478261,0.000374413,0.000005483243],"category_scores_gemma":[0.0003013096,0.0003943379,0.0001429358,0.0007948107,0.0002366484,0.0007630798,0.0009081735,0.0005430121,9.541459e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001976994,"about_ca_system_score_gemma":0.000228105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003140212,"about_ca_topic_score_gemma":0.00002717921,"domain_scores_codex":[0.9970507,0.00008157048,0.0006814339,0.001092166,0.000551607,0.0005425403],"domain_scores_gemma":[0.9969207,0.0009825638,0.0006014935,0.0009885516,0.0004322156,0.00007446483],"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":[0.0000101909,0.000006689724,0.000007151875,0.00003477093,0.000007091213,0.000001797062,0.0001216219,0.5917231,0.00001412191,0.04543673,0.000005178432,0.3626316],"study_design_scores_gemma":[0.0003653736,0.0001160445,0.00009462371,0.0001222979,0.00001750844,0.000008515998,1.143173e-7,0.9667096,0.0001407564,0.03200413,0.0000902626,0.0003307347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00000613367,0.0001481956,0.9961878,0.0003791003,0.002056424,0.0006586291,0.000003368713,0.0003706159,0.0001897094],"genre_scores_gemma":[0.08351884,0.000008156149,0.915713,0.0003864896,0.0002466073,0.00002198115,0.00003225004,0.00002206992,0.00005062892],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3749865,"threshold_uncertainty_score":0.9998509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152814496175352,"score_gpt":0.2806651310954112,"score_spread":0.2691369861336577,"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."}}