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2002.10733
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(De)Randomized Smoothing for Certifiable Defense against Patch Attacks
Neural Information Processing Systems (NeurIPS), 2020
25 February 2020
Alexander Levine
Soheil Feizi
AAML
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Papers citing
"(De)Randomized Smoothing for Certifiable Defense against Patch Attacks"
50 / 97 papers shown
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166
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Tight Robustness Certification Through the Convex Hull of
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224
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13 Nov 2025
Filtered-ViT: A Robust Defense Against Multiple Adversarial Patch Attacks
Aja Khanal
Ahmed Faid
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183
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11 Nov 2025
Provably Robust Adaptation for Language-Empowered Foundation Models
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Xiaoyu Xue
Linghui Shen
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Song Guo
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206
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Reconcile Certified Robustness and Accuracy for DNN-based Smoothed Majority Vote Classifier
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177
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FlyTrap: Physical Distance-Pulling Attack Towards Camera-based Autonomous Target Tracking Systems
Shaoyuan Xie
Mohamad Fakih
Junchi Lu
Fayzah Alshammari
Ningfei Wang
Takami Sato
Halima Bouzidi
Mohammad Abdullah Al Faruque
Qi Alfred Chen
AAML
227
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24 Sep 2025
Backdoor Attacks and Defenses in Computer Vision Domain: A Survey
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Y. Zhang
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193
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09 Sep 2025
IPG: Incremental Patch Generation for Generalized Adversarial Patch Training
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Hyunsik Na
Jisu Lee
Daeseon Choi
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219
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Scalable and Precise Patch Robustness Certification for Deep Learning Models with Top-k Predictions
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Haipeng Wang
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169
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Paul Montague
S. Erfani
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303
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PatchDEMUX: A Certifiably Robust Framework for Multi-label Classifiers Against Adversarial Patches
Computer Vision and Pattern Recognition (CVPR), 2025
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Chong Xiang
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237
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Yizhou Sun
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354
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Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers
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Ronghui Mu
Xiaowei Huang
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395
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21 Mar 2025
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401
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306
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Asia-Pacific Computer Systems Architecture Conference (ACSA), 2024
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Kenechukwu Nwodo
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Angelos Stavrou
Haining Wang
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365
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20 Sep 2024
Certified Adversarial Robustness via Partition-based Randomized Smoothing
Hossein Goli
Farzan Farnia
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300
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Qiang Li
Jinyuan Jia
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271
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Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness
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390
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Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
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376
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Can Implicit Bias Imply Adversarial Robustness?
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389
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351
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181
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CrossCert: A Cross-Checking Detection Approach to Patch Robustness Certification for Deep Learning Models
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Zhengyuan Wei
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Bo Jiang
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328
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Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
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Giulio Zizzo
Quan Le
Jordi Planes
Battista Biggio
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298
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Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research
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209
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BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks
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Zhaoyi Liu
Tengda Guo
Shiwei Feng
Dongfang Liu
Mingjie Tang
Xiangyu Zhang
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427
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A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing
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Giulio Zizzo
Quan Le
Jordi Planes
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275
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Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
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Kshitiz Kaushik
Sarthak Gupta
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379
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Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks
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Amira Guesmi
Mohamed Bennai
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321
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Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception
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Sri Hrushikesh Varma Bhupathiraju
Michael Clifford
Takeshi Sugawara
Qi Alfred Chen
Sara Rampazzi
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Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIP
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225
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367
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441
11
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DefensiveDR: Defending against Adversarial Patches using Dimensionality Reduction
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237
4
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ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches
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Amira Guesmi
Muhammad Abdullah Hanif
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345
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Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches
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Jiachun Li
Changqing Miao
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Wei You
Wenchang Shi
Bin Liang
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363
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Assist Is Just as Important as the Goal: Image Resurfacing to Aid Model's Robust Prediction
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Phil Munz
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319
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Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow
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Andrés Bruhn
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278
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Stephan Günnemann
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599
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PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
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477
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334
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279
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316
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167
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337
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