{"id":"W4401878944","doi":"10.1109/tiv.2024.3449830","title":"AVATAR: Autonomous Vehicle Assessment Through Testing of Adversarial Patches in Real-Time","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Avatar; Adversarial system; Computer science; Human–computer interaction; Computer security; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005839309,0.0002794661,0.0003430513,0.0003324189,0.0001597232,0.0001523003,0.0007274555,0.0001433898,0.0000993314],"category_scores_gemma":[0.00002883084,0.0002786566,0.0001667668,0.001016177,0.0001125087,0.000775822,0.00001829548,0.0006772351,0.0001244221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003279835,"about_ca_system_score_gemma":0.0003027043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119035,"about_ca_topic_score_gemma":0.00004861176,"domain_scores_codex":[0.9976129,0.0002069705,0.0006630341,0.0006579378,0.0004581001,0.0004010705],"domain_scores_gemma":[0.9980925,0.001100546,0.0001151564,0.0005373153,0.00008077387,0.00007375589],"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":[0.00005679972,0.0004086405,0.0003702983,0.0001357973,0.000117331,0.0001003251,0.003696477,0.7507322,0.03989567,0.005356338,0.00006468182,0.1990654],"study_design_scores_gemma":[0.0002928734,0.0002916008,0.0003502097,0.0003635716,0.00003415825,0.00001247995,0.0001830433,0.8780769,0.1170561,0.002581062,0.0004217225,0.0003363983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08084205,0.00005543795,0.9150907,0.00035098,0.001182567,0.000260808,0.00001316322,0.0005184178,0.001685844],"genre_scores_gemma":[0.9002897,0.00006367766,0.09923623,0.00003929349,0.0000818849,0.00003444919,0.000001868697,0.00003387496,0.0002190558],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8194476,"threshold_uncertainty_score":0.9999666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03510320069235098,"score_gpt":0.3060655858895797,"score_spread":0.2709623851972288,"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."}}