{"id":"W4404915790","doi":"10.1109/icipcw64161.2024.10769168","title":"SLACK: Attacking LiDAR-Based SLAM with Adversarial Point Injections","year":2024,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Adversarial system; Lidar; Point (geometry); Computer science; Simultaneous localization and mapping; Artificial intelligence; Computer vision; Point cloud; Remote sensing; Mobile robot; Robot; Mathematics; Geology","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":[0.000374165,0.000217926,0.0001730988,0.0002746931,0.0002751311,0.0005976291,0.0006556206,0.00008269277,0.0002153604],"category_scores_gemma":[0.00009039824,0.0001711109,0.00009732924,0.001052104,0.0000708431,0.0009522105,0.0002453412,0.0004897247,0.0002159513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001340906,"about_ca_system_score_gemma":0.0003571266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001511497,"about_ca_topic_score_gemma":0.00006855385,"domain_scores_codex":[0.9982725,0.00009796451,0.0002212384,0.0006233957,0.0004106983,0.0003741609],"domain_scores_gemma":[0.9989249,0.0002893308,0.00004863436,0.0005573469,0.00007867139,0.0001011139],"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":[0.00007363085,0.0001079422,0.002310919,0.0001140997,0.0001750307,0.0004870326,0.00217073,0.4129116,0.0005157845,0.5263697,0.004158036,0.05060548],"study_design_scores_gemma":[0.0005756412,0.0002144948,0.0004441852,0.0001310136,0.00002773268,0.00005903526,0.00009330171,0.9795729,0.0007035544,0.00143982,0.01635121,0.0003871129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002622274,0.000042521,0.9667011,0.00313184,0.001599276,0.0001659731,0.000001030941,0.001572115,0.02416385],"genre_scores_gemma":[0.8234537,8.667149e-7,0.1745904,0.000350336,0.0003774583,0.00001489505,0.000003522781,0.00002867427,0.001180148],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8208315,"threshold_uncertainty_score":0.6977701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009734349011117293,"score_gpt":0.2569873151186532,"score_spread":0.2472529661075359,"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."}}