{"total":22,"rows":[{"id":"2108.09135","title":"PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier","created":"2021-08-20","cited_by_count":65,"area":null},{"id":"2110.07719","title":"Certified Patch Robustness via Smoothed Vision Transformers","created":"2021-10-11","cited_by_count":45,"area":null},{"id":"2203.08519","title":"Towards Practical Certifiable Patch Defense with Vision Transformer","created":"2022-03-16","cited_by_count":44,"area":null},{"id":"2104.12609","title":"PatchGuard++: Efficient Provable Attack Detection against Adversarial Patches","created":"2021-04-26","cited_by_count":29,"area":null},{"id":"2202.01811","title":"ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking","created":"2022-02-03","cited_by_count":22,"area":null},{"id":"2206.08304","title":"Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey","created":"2022-06-16","cited_by_count":17,"area":null},{"id":"2209.05980","title":"Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation","created":"2022-09-13","cited_by_count":16,"area":null},{"id":"2111.10481","title":"PatchCensor: Patch Robustness Certification for Transformers via Exhaustive Testing","created":"2021-11-19","cited_by_count":12,"area":null},{"id":"2211.01671","title":"Visual Adversarial Attacks and Defenses in the Physical World: A Survey","created":"2022-11-03","cited_by_count":11,"area":null},{"id":"2310.13076","title":"PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses","created":"2023-10-19","cited_by_count":11,"area":null},{"id":"2311.01473","title":"Adversarial Examples in the Physical World: A Survey","created":"2023-11-01","cited_by_count":10,"area":null},{"id":"2204.13004","title":"Defending Person Detection Against Adversarial Patch Attack by using Universal Defensive Frame","created":"2022-04-27","cited_by_count":9,"area":null},{"id":"2306.12610","title":"Revisiting Image Classifier Training for Improved Certified Robust Defense against Adversarial Patches","created":"2023-06-22","cited_by_count":6,"area":null},{"id":"2405.07668","title":"CrossCert: A Cross-Checking Detection Approach to Patch Robustness Certification for Deep Learning Models","created":"2024-05-13","cited_by_count":3,"area":null},{"id":"2303.08944","title":"Agnostic Multi-Robust Learning Using ERM","created":"2023-03-15","cited_by_count":2,"area":null},{"id":"2308.00452","title":"A Majority Invariant Approach to Patch Robustness Certification for Deep Learning Models","created":"2023-08-01","cited_by_count":2,"area":null},{"id":"2511.09834","title":"CertMask: Certifiable Defense Against Adversarial Patches via Theoretically Optimal Mask Coverage","created":"2025-11-13","cited_by_count":2,"area":null},{"id":"2305.10929","title":"Architecture-agnostic Iterative Black-box Certified Defense against Adversarial Patches","created":"2023-05-18","cited_by_count":1,"area":null},{"id":"2505.24703","title":"PatchDEMUX: A Certifiably Robust Framework for Multi-label Classifiers Against Adversarial Patches","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2402.04660","title":"Redesigning Traffic Signs to Mitigate Machine-Learning Patch Attacks","created":"2024-02-07","cited_by_count":0,"area":null},{"id":"2507.23335","title":"Scalable and Precise Patch Robustness Certification for Deep Learning Models with Top-k Predictions","created":"2025-07-31","cited_by_count":0,"area":null},{"id":"2610.10617","title":"MRCert: Towards Post-deployment Patch Robustness Certification for Adversarially Patched Samples via Type-specific Masking","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}