Bag of Tricks for Adversarial Training

1 October 2020

Tianyu Pang

Xiao Yang

Yinpeng Dong

Hang Su

Jun Zhu

AAML

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Papers citing "Bag of Tricks for Adversarial Training"

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Title
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models Xiaojun Jia Sensen Gao Simeng Qin Ke Ma Xianrui Li Yihao Huang Wei Dong Yang Liu Xiaochun Cao AAML VLM 60 0 0 17 Mar 2025
Long-tailed Adversarial Training with Self-Distillation Seungju Cho Hongsin Lee Changick Kim AAML TTA 209 0 0 09 Mar 2025
Dynamic Guidance Adversarial Distillation with Enhanced Teacher Knowledge Hyejin Park Dongbo Min AAML 42 2 0 03 Sep 2024
Benchmarking the Robustness of Temporal Action Detection Models Against Temporal Corruptions Runhao Zeng Xiaoyong Chen Jiaming Liang Huisi Wu Guangzhong Cao Yong Guo AAML 39 3 0 29 Mar 2024
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape Tiejin Chen Wenwang Huang Linsey Pang Dongsheng Luo Hua Wei OOD 49 0 0 09 Mar 2024
Indirect Gradient Matching for Adversarial Robust Distillation Hongsin Lee Seungju Cho Changick Kim AAML FedML 53 2 0 06 Dec 2023
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 28 2 0 09 Nov 2023
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Yifei Wang Liangchen Li Jiansheng Yang Zhouchen Lin Yisen Wang 31 11 0 30 Oct 2023
On the Importance of Backbone to the Adversarial Robustness of Object Detectors Xiao-Li Li Hang Chen Xiaolin Hu AAML 38 4 0 27 May 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 43 50 0 18 May 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 15 0 0 29 Mar 2023
CAT:Collaborative Adversarial Training Xingbin Liu Huafeng Kuang Xianming Lin Yongjian Wu Rongrong Ji AAML 22 4 0 27 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 44 34 0 19 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 33 72 0 28 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 24 208 0 09 Feb 2023
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection Mohammad Azizmalayeri Arman Zarei Alireza Isavand M. T. Manzuri M. Rohban OODD 35 0 0 25 Jan 2023
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli Fahad Shahbaz Khan AAML 28 1 0 30 Dec 2022
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models Chengzhi Mao Scott Geng Junfeng Yang Xin Eric Wang Carl Vondrick VLM 44 59 0 14 Dec 2022
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 24 5 0 26 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds Sravanti Addepalli Samyak Jain Gaurang Sriramanan R. Venkatesh Babu AAML 33 22 0 18 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Yi Mo Dongxian Wu Yifei Wang Yiwen Guo Yisen Wang ViT 45 52 0 14 Oct 2022
Towards Out-of-Distribution Adversarial Robustness Adam Ibrahim Charles Guille-Escuret Ioannis Mitliagkas Irina Rish David M. Krueger P. Bashivan OOD 31 6 0 06 Oct 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training Saehyung Lee Hyungyu Lee AAML 29 2 0 27 Sep 2022
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 32 68 0 15 Sep 2022
Bag of Tricks for FGSM Adversarial Training Zichao Li Li Liu Zeyu Wang Yuyin Zhou Cihang Xie AAML 33 6 0 06 Sep 2022
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness Chaoning Zhang Kang Zhang Chenshuang Zhang Axi Niu Jiu Feng Chang D. Yoo In So Kweon SSL 35 24 0 22 Jul 2022
Boosting the Adversarial Transferability of Surrogate Models with Dark Knowledge Dingcheng Yang Zihao Xiao Wenjian Yu AAML 36 5 0 16 Jun 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 19 2 0 08 Jun 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 45 15 0 07 Jun 2022
Case-Aware Adversarial Training Mingyuan Fan Yang Liu Ximeng Liu AAML 24 1 0 20 Apr 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning Mathias Lechner Alexander Amini Daniela Rus T. Henzinger AAML 29 9 0 15 Apr 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 29 47 0 11 Mar 2022
Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation Xiaogeng Liu Haoyu Wang Yechao Zhang Fangzhou Wu Shengshan Hu OOD 27 11 0 08 Mar 2022
Global-Local Regularization Via Distributional Robustness Hoang Phan Trung Le Trung-Nghia Phung Tu Bui Nhat Ho Dinh Q. Phung OOD 22 12 0 01 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 31 42 0 27 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks Yinghua Gao Dongxian Wu Jingfeng Zhang Guanhao Gan Shutao Xia Gang Niu Masashi Sugiyama AAML 32 22 0 22 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min-Bin Lin Xiao Yang Junyi Zhu Shuicheng Yan 30 119 0 21 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen Zhenyu (Allen) Zhang Pengju Wang Santosh Balachandra Haoyu Ma Zehao Wang Zhangyang Wang OOD AAML 85 47 0 20 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 98 16 0 31 Jan 2022
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 27 15 0 30 Jan 2022
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Mengting Xu Tao Zhang Zhongnian Li Daoqiang Zhang AAML 38 1 0 29 Jan 2022
Can Model Compression Improve NLP Fairness Guangxuan Xu Qingyuan Hu 31 26 0 21 Jan 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 197 345 0 15 Dec 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 43 17 0 09 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training Erh-Chung Chen Che-Rung Lee AAML 24 26 0 03 Nov 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 36 293 0 18 Oct 2021
Parameterizing Activation Functions for Adversarial Robustness Sihui Dai Saeed Mahloujifar Prateek Mittal AAML 42 32 0 11 Oct 2021
Adversarial Token Attacks on Vision Transformers Ameya Joshi Gauri Jagatap C. Hegde ViT 30 19 0 08 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
LibFewShot: A Comprehensive Library for Few-shot Learning Wenbin Li Ziyi Ziyi Wang Xuesong Yang C. Dong ... Jing Huo Yinghuan Shi Lei Wang Yang Gao Jiebo Luo VLM 113 66 0 10 Sep 2021