Overfitting in adversarially robust deep learning

26 February 2020

Papers citing "Overfitting in adversarially robust deep learning"

50 / 156 papers shown

Title
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data Lilin Zhang Chengpei Wu Ning Yang 34 0 0 14 Mar 2025
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions Wang YuHang Junkang Guo Aolei Liu Kaihao Wang Zaitong Wu Zhenyu Liu Wenfei Yin Jian Liu AAML 48 0 0 02 Mar 2025
HALO: Robust Out-of-Distribution Detection via Joint Optimisation Hugo Lyons Keenan S. Erfani Christopher Leckie OODD 202 0 0 27 Feb 2025
Differentiable Adversarial Attacks for Marked Temporal Point Processes Pritish Chakraborty Vinayak Gupta R. Raj Srikanta J. Bedathur A. De AAML 169 0 0 17 Jan 2025
Evaluating Concurrent Robustness of Language Models Across Diverse Challenge Sets Vatsal Gupta Pranshu Pandya Tushar Kataria Vivek Gupta Dan Roth AAML 55 1 0 03 Jan 2025
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training Tejaswini Medi Steffen Jung M. Keuper AAML 36 3 0 30 Oct 2024
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 33 2 0 09 Oct 2024
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 33 1 0 02 Oct 2024
Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness Hefei Mei Minjing Dong Chang Xu AAML 51 0 0 16 Aug 2024
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness Kejia Zhang Juanjuan Weng Yuanzheng Cai Zhiming Luo Shaozi Li AAML 59 0 0 04 Jul 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers Jonas Ngnawé Sabyasachi Sahoo Y. Pequignot Frédéric Precioso Christian Gagné AAML 36 0 0 26 Jun 2024
MEAT: Median-Ensemble Adversarial Training for Improving Robustness and Generalization Zhaozhe Hu Jia-Li Yin Bin Chen Luojun Lin Bo-Hao Chen Ximeng Liu AAML 28 0 0 20 Jun 2024
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness Kejia Zhang Juanjuan Weng Junwei Wu Guoqing Yang Shaozi Li Zhiming Luo AAML 38 1 0 17 Jun 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 40 0 0 03 May 2024
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu Aditya Singh Yijiang Li Haohan Wang AAML ViT 31 1 0 15 Mar 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 37 5 0 11 Mar 2024
Revisiting Confidence Estimation: Towards Reliable Failure Prediction Fei Zhu Xu-Yao Zhang Zhen Cheng Cheng-Lin Liu UQCV 46 10 0 05 Mar 2024
Catastrophic Overfitting: A Potential Blessing in Disguise Mengnan Zhao Lihe Zhang Yuqiu Kong Baocai Yin AAML 39 1 0 28 Feb 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective Yue Xing Xiaofeng Lin Qifan Song Yi Tian Xu Belinda Zeng Guang Cheng SSL 15 0 0 26 Jan 2024
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training Shruthi Gowda Bahram Zonooz Elahe Arani AAML 28 2 0 26 Jan 2024
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Yifei Wang Liangchen Li Jiansheng Yang Zhouchen Lin Yisen Wang 23 11 0 30 Oct 2023
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Boya Zhang Weijian Luo Zhihua Zhang 29 10 0 28 Oct 2023
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin Chaojian Yu Bo Han Tongliang Liu 22 7 0 13 Oct 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization Jiancong Xiao Ruoyu Sun Zhimin Luo AAML 30 6 0 09 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 40 1 0 06 Oct 2023
Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow Sen-Fon Lin Zhangyang Wang Yitao Liang AAML OOD 33 2 0 01 Aug 2023
Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training Yechao Zhang Shengshan Hu Leo Yu Zhang Junyu Shi Minghui Li Xiaogeng Liu Wei Wan Hai Jin AAML 22 21 0 15 Jul 2023
Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning Byung-Kwan Lee Junho Kim Yonghyun Ro AAML 12 9 0 14 Jul 2023
Omnipotent Adversarial Training in the Wild Guanlin Li Kangjie Chen Yuan Xu Han Qiu Tianwei Zhang 16 0 0 14 Jul 2023
Enhancing Adversarial Robustness via Score-Based Optimization Boya Zhang Weijian Luo Zhihua Zhang DiffM 21 12 0 10 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 22 1 0 29 Jun 2023
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations Y. Fu Ye Yuan Souvik Kundu Shang Wu Shunyao Zhang Yingyan Lin AAML 60 6 0 10 Jun 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 34 49 0 18 May 2023
Exploiting Frequency Spectrum of Adversarial Images for General Robustness Chun Yang Tan K. Kawamoto Hiroshi Kera AAML OOD 26 1 0 15 May 2023
Token-Level Fitting Issues of Seq2seq Models Guangsheng Bao Zhiyang Teng Yue Zhang 16 0 0 08 May 2023
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 27 4 0 06 Apr 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 13 0 0 29 Mar 2023
CAT:Collaborative Adversarial Training Xingbin Liu Huafeng Kuang Xianming Lin Yongjian Wu Rongrong Ji AAML 17 4 0 27 Mar 2023
PIAT: Parameter Interpolation based Adversarial Training for Image Classification Kun He Xin Liu Yichen Yang Zhou Qin Weigao Wen Hui Xue J. Hopcroft AAML 22 0 0 24 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 36 34 0 19 Mar 2023
Rethinking Confidence Calibration for Failure Prediction Fei Zhu Zhen Cheng Xu-Yao Zhang Cheng-Lin Liu UQCV 14 39 0 06 Mar 2023
Certified Robust Neural Networks: Generalization and Corruption Resistance Amine Bennouna Ryan Lucas Bart P. G. Van Parys 32 10 0 03 Mar 2023
DSD $^2$ : Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? Victor Quétu Enzo Tartaglione 24 7 0 02 Mar 2023
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression Junho Kim Byung-Kwan Lee Yonghyun Ro CML AAML 20 18 0 02 Mar 2023
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking Chang-Shu Liu Yinpeng Dong Wenzhao Xiang X. Yang Hang Su Junyi Zhu YueFeng Chen Yuan He H. Xue Shibao Zheng OOD VLM AAML 27 72 0 28 Feb 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 21 7 0 21 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 16 207 0 09 Feb 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations Hassan Dbouk Naresh R Shanbhag AAML 23 7 0 02 Feb 2023
Language-Driven Anchors for Zero-Shot Adversarial Robustness Xiao-Li Li Wei Emma Zhang Yining Liu Zhan Hu Bo-Wen Zhang Xiaolin Hu 26 8 0 30 Jan 2023
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks Jona Klemenc Holger Trittenbach AAML 24 1 0 28 Jan 2023