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2020 – today
- 2024
[c39]Zhaorui Yang, Tianyu Pang, Haozhe Feng, Han Wang, Wei Chen, Minfeng Zhu, Qian Liu:
Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning. ACL (1) 2024: 1028-1043- [c38]Haozhe Feng, Tianyu Pang, Chao Du, Wei Chen, Shuicheng Yan, Min Lin:
BAFFLE: A Baseline of Backpropagation-Free Federated Learning. ECCV (75) 2024: 89-109 - [c37]Zihang Liu, Yuanzhe Hu, Tianyu Pang, Yefan Zhou, Pu Ren, Yaoqing Yang:
Model Balancing Helps Low-data Training and Fine-tuning. EMNLP 2024: 1311-1331 - [c36]Xudong Shen, Chao Du, Tianyu Pang, Min Lin, Yongkang Wong, Mohan S. Kankanhalli:
Finetuning Text-to-Image Diffusion Models for Fairness. ICLR 2024 - [c35]Xiaosen Zheng, Tianyu Pang, Chao Du, Jing Jiang, Min Lin:
Intriguing Properties of Data Attribution on Diffusion Models. ICLR 2024 - [c34]Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, Min Lin:
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast. ICML 2024 - [i70]Jiawei Zhang, Tianyu Pang
, Chao Du, Yi Ren, Bo Li, Min Lin:
Benchmarking Large Multimodal Models against Common Corruptions. CoRR abs/2401.11943 (2024) - [i69]Xuandong Zhao, Xianjun Yang, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, William Yang Wang:
Weak-to-Strong Jailbreaking on Large Language Models. CoRR abs/2401.17256 (2024) - [i68]Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, Min Lin:
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast. CoRR abs/2402.08567 (2024) - [i67]Dong Lu, Tianyu Pang, Chao Du, Qian Liu, Xianjun Yang, Min Lin:
Test-Time Backdoor Attacks on Multimodal Large Language Models. CoRR abs/2402.08577 (2024) - [i66]Tianlin Li, Xiaoyu Zhang, Chao Du, Tianyu Pang, Qian Liu, Qing Guo, Chao Shen, Yang Liu:
Your Large Language Model is Secretly a Fairness Proponent and You Should Prompt it Like One. CoRR abs/2402.12150 (2024) - [i65]Zhaorui Yang, Qian Liu, Tianyu Pang, Han Wang, Haozhe Feng, Minfeng Zhu, Wei Chen:
Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning. CoRR abs/2402.13669 (2024) - [i64]Tianlin Li, Qian Liu, Tianyu Pang, Chao Du, Qing Guo, Yang Liu, Min Lin:
Purifying Large Language Models by Ensembling a Small Language Model. CoRR abs/2402.14845 (2024) - [i63]Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Wei Chen, Min Lin:
Graph Diffusion Policy Optimization. CoRR abs/2402.16302 (2024) - [i62]Xiaojun Jia, Tianyu Pang, Chao Du, Yihao Huang, Jindong Gu, Yang Liu, Xiaochun Cao, Min Lin:
Improved Techniques for Optimization-Based Jailbreaking on Large Language Models. CoRR abs/2405.21018 (2024) - [i61]Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Jing Jiang, Min Lin:
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses. CoRR abs/2406.01288 (2024) - [i60]Vignesh Kothapalli, Tianyu Pang, Shenyang Deng, Zongmin Liu, Yaoqing Yang:
Crafting Heavy-Tails in Weight Matrix Spectrum without Gradient Noise. CoRR abs/2406.04657 (2024) - [i59]Xuan Zhang, Chao Du, Tianyu Pang, Qian Liu, Wei Gao, Min Lin:
Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs. CoRR abs/2406.09136 (2024) - [i58]Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin:
Bootstrapping Language Models with DPO Implicit Rewards. CoRR abs/2406.09760 (2024) - [i57]Siyuan Liang, Jiawei Liang, Tianyu Pang, Chao Du, Aishan Liu, Ee-Chien Chang, Xiaochun Cao:
Revisiting Backdoor Attacks against Large Vision-Language Models. CoRR abs/2406.18844 (2024) - [i56]Qian Liu, Xiaosen Zheng, Niklas Muennighoff, Guangtao Zeng, Longxu Dou, Tianyu Pang, Jing Jiang, Min Lin:
RegMix: Data Mixture as Regression for Language Model Pre-training. CoRR abs/2407.01492 (2024) - [i55]Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Jing Jiang, Min Lin:
Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates. CoRR abs/2410.07137 (2024) - [i54]Xiaojian Yuan, Tianyu Pang, Chao Du, Kejiang Chen, Weiming Zhang, Min Lin:
A Closer Look at Machine Unlearning for Large Language Models. CoRR abs/2410.08109 (2024) - [i53]Kuofeng Gao, Tianyu Pang, Chao Du, Yong Yang, Shu-Tao Xia, Min Lin:
Denial-of-Service Poisoning Attacks against Large Language Models. CoRR abs/2410.10760 (2024) - [i52]Xiangming Gu, Tianyu Pang, Chao Du, Qian Liu, Fengzhuo Zhang, Cunxiao Du, Ye Wang, Min Lin:
When Attention Sink Emerges in Language Models: An Empirical View. CoRR abs/2410.10781 (2024) - [i51]Luping Liu, Chao Du, Tianyu Pang, Zehan Wang, Chongxuan Li, Dong Xu:
Improving Long-Text Alignment for Text-to-Image Diffusion Models. CoRR abs/2410.11817 (2024) - [i50]Zihang Liu, Yuanzhe Hu, Tianyu Pang, Yefan Zhou, Pu Ren, Yaoqing Yang:
Model Balancing Helps Low-data Training and Fine-tuning. CoRR abs/2410.12178 (2024) - [i49]Hongcheng Gao, Tianyu Pang, Chao Du, Taihang Hu, Zhijie Deng, Min Lin:
Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts. CoRR abs/2410.12777 (2024) - [i48]Xuan Zhang, Cunxiao Du, Chao Du, Tianyu Pang, Wei Gao, Min Lin:
SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction. CoRR abs/2410.13846 (2024) - [i47]Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, Chongxuan Li:
Scaling up Masked Diffusion Models on Text. CoRR abs/2410.18514 (2024) - 2023
- [c33]Yunqing Zhao, Chao Du, Milad Abdollahzadeh, Tianyu Pang, Min Lin, Shuicheng Yan, Ngai-Man Cheung:
Exploring Incompatible Knowledge Transfer in Few-shot Image Generation. CVPR 2023: 7380-7391 - [c32]Chao Du, Tianbo Li, Tianyu Pang, Shuicheng Yan, Min Lin:
Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows. ICML 2023: 8565-8584 - [c31]Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan:
Better Diffusion Models Further Improve Adversarial Training. ICML 2023: 36246-36263 - [c30]Zonghan Yang, Peng Li, Tianyu Pang, Yang Liu:
Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics. ICML 2023: 39349-39364 - [c29]Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang, Yan Huang, Min Lin, Shuicheng Yan:
Bag of Tricks for Training Data Extraction from Language Models. ICML 2023: 40306-40320 - [c28]Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li:
Gaussian Mixture Solvers for Diffusion Models. NeurIPS 2023 - [c27]Bingyi Kang, Xiao Ma, Chao Du, Tianyu Pang, Shuicheng Yan:
Efficient Diffusion Policies For Offline Reinforcement Learning. NeurIPS 2023 - [c26]Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng:
On Calibrating Diffusion Probabilistic Models. NeurIPS 2023 - [c25]Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin:
On Evaluating Adversarial Robustness of Large Vision-Language Models. NeurIPS 2023 - [c24]Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang:
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. NeurIPS 2023 - [i46]Haozhe Feng, Tianyu Pang, Chao Du, Wei Chen, Shuicheng Yan, Min Lin:
Does Federated Learning Really Need Backpropagation? CoRR abs/2301.12195 (2023) - [i45]Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang, Yan Huang, Min Lin, Shuicheng Yan:
Bag of Tricks for Training Data Extraction from Language Models. CoRR abs/2302.04460 (2023) - [i44]Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan:
Better Diffusion Models Further Improve Adversarial Training. CoRR abs/2302.04638 (2023) - [i43]Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng:
On Calibrating Diffusion Probabilistic Models. CoRR abs/2302.10688 (2023) - [i42]Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Ngai-Man Cheung, Min Lin:
A Recipe for Watermarking Diffusion Models. CoRR abs/2303.10137 (2023) - [i41]Haozhe Feng, Zhaorui Yang, Hesun Chen, Tianyu Pang, Chao Du, Minfeng Zhu, Wei Chen, Shuicheng Yan:
CoSDA: Continual Source-Free Domain Adaptation. CoRR abs/2304.06627 (2023) - [i40]Yunqing Zhao, Chao Du, Milad Abdollahzadeh, Tianyu Pang, Min Lin, Shuicheng Yan, Ngai-Man Cheung:
Exploring Incompatible Knowledge Transfer in Few-shot Image Generation. CoRR abs/2304.07574 (2023) - [i39]Chao Du, Tianbo Li, Tianyu Pang, Shuicheng Yan, Min Lin:
Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows. CoRR abs/2305.02164 (2023) - [i38]Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin:
On Evaluating Adversarial Robustness of Large Vision-Language Models. CoRR abs/2305.16934 (2023) - [i37]Bingyi Kang, Xiao Ma, Chao Du, Tianyu Pang, Shuicheng Yan:
Efficient Diffusion Policies for Offline Reinforcement Learning. CoRR abs/2305.20081 (2023) - [i36]Zonghan Yang, Tianyu Pang, Yang Liu:
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models. CoRR abs/2306.01429 (2023) - [i35]Zonghan Yang, Peng Li, Tianyu Pang, Yang Liu:
Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics. CoRR abs/2306.01435 (2023) - [i34]Chengsong Huang, Qian Liu, Bill Yuchen Lin, Tianyu Pang, Chao Du, Min Lin:
LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition. CoRR abs/2307.13269 (2023) - [i33]Xiangming Gu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Ye Wang:
On Memorization in Diffusion Models. CoRR abs/2310.02664 (2023) - [i32]Xiaosen Zheng, Tianyu Pang, Chao Du, Jing Jiang, Min Lin:
Intriguing Properties of Data Attribution on Diffusion Models. CoRR abs/2311.00500 (2023) - [i31]Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li:
Gaussian Mixture Solvers for Diffusion Models. CoRR abs/2311.00941 (2023) - [i30]Xudong Shen, Chao Du, Tianyu Pang, Min Lin, Yongkang Wong, Mohan S. Kankanhalli:
Finetuning Text-to-Image Diffusion Models for Fairness. CoRR abs/2311.07604 (2023) - [i29]Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang:
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. CoRR abs/2312.00359 (2023) - 2022
- [j1]Yinpeng Dong, Shuyu Cheng, Tianyu Pang, Hang Su, Jun Zhu:
Query-Efficient Black-Box Adversarial Attacks Guided by a Transfer-Based Prior. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9536-9548 (2022) - [c23]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR 2022: 15202-15212 - [c22]Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks. ECCV (4) 2022: 725-742 - [c21]Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu:
Exploring Memorization in Adversarial Training. ICLR 2022 - [c20]Tianyu Pang, Min Lin, Xiao Yang, Jun Zhu, Shuicheng Yan:
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition. ICML 2022: 17258-17277 - [c19]Zonghan Yang, Tianyu Pang, Yang Liu:
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models. NeurIPS 2022 - [i28]Tianyu Pang, Min Lin, Xiao Yang, Jun Zhu, Shuicheng Yan:
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition. CoRR abs/2202.10103 (2022) - [i27]Xiao Yang, Yinpeng Dong, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu:
Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition. CoRR abs/2203.04623 (2022) - [i26]Yinpeng Dong, Shuyu Cheng, Tianyu Pang, Hang Su, Jun Zhu:
Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based Prior. CoRR abs/2203.06560 (2022) - [i25]Tianyu Pang, Shuicheng Yan, Min Lin:
O(N2) Universal Antisymmetry in Fermionic Neural Networks. CoRR abs/2205.13205 (2022) - 2021
- [c18]Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu, Yuefeng Chen, Hui Xue:
Towards Face Encryption by Generating Adversarial Identity Masks. ICCV 2021: 3877-3887 - [c17]Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu:
Black-box Detection of Backdoor Attacks with Limited Information and Data. ICCV 2021: 16462-16471 - [c16]Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu:
Bag of Tricks for Adversarial Training. ICLR 2021 - [c15]Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu:
Accumulative Poisoning Attacks on Real-time Data. NeurIPS 2021: 2899-2912 - [i24]Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu:
Black-box Detection of Backdoor Attacks with Limited Information and Data. CoRR abs/2103.13127 (2021) - [i23]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Adversarial Training with Rectified Rejection. CoRR abs/2105.14785 (2021) - [i22]Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu:
Exploring Memorization in Adversarial Training. CoRR abs/2106.01606 (2021) - [i21]Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu:
Accumulative Poisoning Attacks on Real-time Data. CoRR abs/2106.09993 (2021) - [i20]Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks. CoRR abs/2107.01809 (2021) - [i19]Yinpeng Dong, Qi-An Fu, Xiao Yang, Wenzhao Xiang, Tianyu Pang, Hang Su, Jun Zhu, Jiayu Tang, Yuefeng Chen, Xiaofeng Mao, Yuan He, Hui Xue, Chao Li, Ye Liu, Qilong Zhang, Lianli Gao, Yunrui Yu, Xitong Gao, Zhe Zhao, Daquan Lin, Jiadong Lin, Chuanbiao Song, Zihao Wang, Zhennan Wu, Yang Guo, Jiequan Cui, Xiaogang Xu, Pengguang Chen:
Adversarial Attacks on ML Defense Models Competition. CoRR abs/2110.08042 (2021) - [i18]Xiao Yang, Yinpeng Dong, Wenzhao Xiang, Tianyu Pang, Hang Su, Jun Zhu:
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness. CoRR abs/2110.08256 (2021) - [i17]Yuefeng Chen, Xiaofeng Mao, Yuan He, Hui Xue, Chao Li, Yinpeng Dong, Qi-An Fu, Xiao Yang, Wenzhao Xiang, Tianyu Pang, Hang Su, Jun Zhu, Fangcheng Liu, Chao Zhang, Hongyang Zhang, Yichi Zhang, Shilong Liu, Chang Liu, Wenzhao Xiang, Yajie Wang, Huipeng Zhou, Haoran Lyu, Yidan Xu, Zixuan Xu, Taoyu Zhu, Wenjun Li, Xianfeng Gao, Guoqiu Wang, Huanqian Yan, Ying Guo, Chaoning Zhang, Zheng Fang, Yang Wang, Bingyang Fu, Yunfei Zheng, Yekui Wang, Haorong Luo, Zhen Yang:
Unrestricted Adversarial Attacks on ImageNet Competition. CoRR abs/2110.09903 (2021) - 2020
- [c14]Yinpeng Dong, Qi-An Fu, Xiao Yang, Tianyu Pang, Hang Su, Zihao Xiao, Jun Zhu:
Benchmarking Adversarial Robustness on Image Classification. CVPR 2020: 318-328 - [c13]Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu:
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. ICLR 2020 - [c12]Tianyu Pang, Kun Xu, Jun Zhu:
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks. ICLR 2020 - [c11]Yinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu, Hang Su:
Adversarial Distributional Training for Robust Deep Learning. NeurIPS 2020 - [c10]Tianyu Pang, Taufik Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu:
Efficient Learning of Generative Models via Finite-Difference Score Matching. NeurIPS 2020 - [c9]Tianyu Pang, Xiao Yang, Yinpeng Dong, Taufik Xu, Jun Zhu, Hang Su:
Boosting Adversarial Training with Hypersphere Embedding. NeurIPS 2020 - [i16]Zhijie Deng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Adversarial Distributional Training for Robust Deep Learning. CoRR abs/2002.05999 (2020) - [i15]Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Hang Su, Jun Zhu:
Boosting Adversarial Training with Hypersphere Embedding. CoRR abs/2002.08619 (2020) - [i14]Xiao Yang, Yinpeng Dong, Tianyu Pang, Jun Zhu, Hang Su:
Towards Privacy Protection by Generating Adversarial Identity Masks. CoRR abs/2003.06814 (2020) - [i13]Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu:
Efficient Learning of Generative Models via Finite-Difference Score Matching. CoRR abs/2007.03317 (2020) - [i12]Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu:
Bag of Tricks for Adversarial Training. CoRR abs/2010.00467 (2020)
2010 – 2019
- 2019
- [c8]Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks. CVPR 2019: 4312-4321 - [c7]Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu:
Improving Adversarial Robustness via Promoting Ensemble Diversity. ICML 2019: 4970-4979 - [c6]Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Improving Black-box Adversarial Attacks with a Transfer-based Prior. NeurIPS 2019: 10932-10942 - [i11]Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu:
Improving Adversarial Robustness via Promoting Ensemble Diversity. CoRR abs/1901.08846 (2019) - [i10]Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks. CoRR abs/1904.02884 (2019) - [i9]Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu:
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. CoRR abs/1905.10626 (2019) - [i8]Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu:
Improving Black-box Adversarial Attacks with a Transfer-based Prior. CoRR abs/1906.06919 (2019) - [i7]Tianyu Pang, Kun Xu, Jun Zhu:
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks. CoRR abs/1909.11515 (2019) - [i6]Yinpeng Dong, Qi-An Fu, Xiao Yang, Tianyu Pang, Hang Su, Zihao Xiao, Jun Zhu:
Benchmarking Adversarial Robustness. CoRR abs/1912.11852 (2019) - 2018
- [c5]Fangzhou Liao, Ming Liang, Yinpeng Dong, Tianyu Pang, Xiaolin Hu, Jun Zhu:
Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser. CVPR 2018: 1778-1787 - [c4]Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, Jianguo Li:
Boosting Adversarial Attacks With Momentum. CVPR 2018: 9185-9193 - [c3]Tianyu Pang, Chao Du, Jun Zhu:
Max-Mahalanobis Linear Discriminant Analysis Networks. ICML 2018: 4013-4022 - [c2]Tianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu:
Towards Robust Detection of Adversarial Examples. NeurIPS 2018: 4584-4594 - [c1]Yu Chen, Sheng Yan, Tianyu Pang, Rui Chen:
Detection of DGA Domains Based on Support Vector Machine. SSIC 2018: 1-4 - [i5]Tianyu Pang, Chao Du, Jun Zhu:
Max-Mahalanobis Linear Discriminant Analysis Networks. CoRR abs/1802.09308 (2018) - [i4]Alexey Kurakin, Ian J. Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan L. Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe:
Adversarial Attacks and Defences Competition. CoRR abs/1804.00097 (2018) - 2017
- [i3]Tianyu Pang, Chao Du, Jun Zhu:
Robust Deep Learning via Reverse Cross-Entropy Training and Thresholding Test. CoRR abs/1706.00633 (2017) - [i2]Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Xiaolin Hu, Jun Zhu:
Discovering Adversarial Examples with Momentum. CoRR abs/1710.06081 (2017) - [i1]Fangzhou Liao, Ming Liang, Yinpeng Dong, Tianyu Pang, Jun Zhu, Xiaolin Hu:
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser. CoRR abs/1712.02976 (2017)
Coauthor Index
[c38] [c36] [c35] [c34] [i70] [i69] [i68] [i67] [i66] [i64] [i63] [i62] [i61] [i59] [i58] [i57] [i55] [i54] [i53] [i52] [i51] [i49] [i48] [i47] [c33] [c32] [c31] [c29] [c28] [c27] [c26] [c25] [i46] [i45] [i44] [i43] [i42] [i41] [i40] [i39] [i38] [i37] [i34] [i33] [i32] [i31] [i30] [c13] [c7] [i11] [i9] [c3] [c2] [i5] [i3]
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