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2020 – today
- 2025
[i38]Rui Min, Tianyu Pang, Chao Du, Qian Liu, Minhao Cheng, Min Lin:
Improving Your Model Ranking on Chatbot Arena by Vote Rigging. CoRR abs/2501.17858 (2025)- [i37]Haoyu Wang, Zeyu Qin, Li Shen, Xueqian Wang, Minhao Cheng, Dacheng Tao:
Leveraging Reasoning with Guidelines to Elicit and Utilize Knowledge for Enhancing Safety Alignment. CoRR abs/2502.04040 (2025) - 2024
- [c38]Dandan Ni
, Sheng Zhang, Cong Deng, Han Liu, Gang Chen, Minhao Cheng, Hongyang Chen:
Exploring Robustness of GNN against Universal Injection Attack from a Worst-case Perspective. CIKM 2024: 1785-1794 - [c37]Rui Min, Sen Li, Hongyang Chen, Minhao Cheng:
A Watermark-Conditioned Diffusion Model for IP Protection. ECCV (69) 2024: 104-120 - [c36]Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Boqing Gong, Cho-Jui Hsieh:
Understanding the Impact of Negative Prompts: When and How Do They Take Effect? ECCV (89) 2024: 190-206 - [c35]Liaoyaqi Wang, Minhao Cheng:
GuardEmb: Dynamic Watermark for Safeguarding Large Language Model Embedding Service Against Model Stealing Attack. EMNLP (Findings) 2024: 7518-7534 - [c34]Liying Li, Yihan Bai, Minhao Cheng:
Where Am I From? Identifying Origin of LLM-generated Content. EMNLP 2024: 12218-12229 - [c33]Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh:
DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers. EMNLP (Findings) 2024: 13891-13913 - [c32]Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng, Xiang Ao:
Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective. ICLR 2024 - [c31]Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh:
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. ICML 2024 - [c30]Haosen Wang, Can Xu, Chenglong Shi, Pengfei Zheng, Shiming Zhang, Minhao Cheng, Hongyang Chen:
Unsupervised Heterogeneous Graph Rewriting Attack via Node Clustering. KDD 2024: 3057-3068 - [c29]Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng:
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. NeurIPS 2024 - [i36]Sen Li, Ruochen Wang, Cho-Jui Hsieh, Minhao Cheng, Tianyi Zhou:
MuLan: Multimodal-LLM Agent for Progressive Multi-Object Diffusion. CoRR abs/2402.12741 (2024) - [i35]Yong Liu, Zirui Zhu, Chaoyu Gong, Minhao Cheng, Cho-Jui Hsieh, Yang You:
Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning. CoRR abs/2402.15751 (2024) - [i34]Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh:
DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers. CoRR abs/2402.16914 (2024) - [i33]Rui Min, Sen Li, Hongyang Chen, Minhao Cheng:
A Watermark-Conditioned Diffusion Model for IP Protection. CoRR abs/2403.10893 (2024) - [i32]QingGuo Qi, Hongyang Chen, Minhao Cheng, Han Liu:
Input Snapshots Fusion for Scalable Discrete Dynamic Graph Nerual Networks. CoRR abs/2405.06975 (2024) - [i31]Sen Li, Junchi Ma, Minhao Cheng:
Invisible Backdoor Attacks on Diffusion Models. CoRR abs/2406.00816 (2024) - [i30]Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-Jui Hsieh, Minhao Cheng:
The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise. CoRR abs/2406.01970 (2024) - [i29]Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Boqing Gong, Cho-Jui Hsieh:
Understanding the Impact of Negative Prompts: When and How Do They Take Effect? CoRR abs/2406.02965 (2024) - [i28]Xirui Li, Hengguang Zhou, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh:
MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries? CoRR abs/2406.17806 (2024) - [i27]Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh:
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. CoRR abs/2407.00256 (2024) - [i26]Xinglin Li, Xianwen He, Yao Li, Minhao Cheng:
Defense Against Syntactic Textual Backdoor Attacks with Token Substitution. CoRR abs/2407.04179 (2024) - [i25]Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng:
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. CoRR abs/2410.09838 (2024) - 2023
- [j2]Jianqiu Wu, Hongyang Chen, Minhao Cheng, Haoyi Xiong:
CurvAGN: Curvature-based Adaptive Graph Neural Networks for Predicting Protein-Ligand Binding Affinity. BMC Bioinform. 24(1): 378 (2023) - [c28]Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix Yu, Cho-Jui Hsieh:
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning. CVPR 2023: 16323-16332 - [c27]Bo Huang, Mingyang Chen, Yi Wang, Junda Lu, Minhao Cheng, Wei Wang:
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation. CVPR 2023: 24668-24677 - [c26]Lichang Chen, Jiuhai Chen, Heng Huang, Minhao Cheng:
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. EMNLP 2023: 13512-13525 - [c25]Minhao Cheng, Rui Min, Haochen Sun, Pin-Yu Chen:
Identification of the Adversary from a Single Adversarial Example. ICML 2023: 5472-5484 - [c24]Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng:
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. KDD 2023: 4743-4755 - [c23]Rui Min, Zeyu Qin, Li Shen, Minhao Cheng:
Towards Stable Backdoor Purification through Feature Shift Tuning. NeurIPS 2023 - [i24]Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng:
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. CoRR abs/2302.01677 (2023) - [i23]Lichang Chen, Heng Huang, Minhao Cheng:
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. CoRR abs/2305.02423 (2023) - [i22]Lichang Chen, Minhao Cheng, Heng Huang:
Backdoor Learning on Sequence to Sequence Models. CoRR abs/2305.02424 (2023) - [i21]Yize Cheng, Wenbin Hu, Minhao Cheng:
Backdoor Attack against Object Detection with Clean Annotation. CoRR abs/2307.10487 (2023) - [i20]Rui Min, Zeyu Qin, Li Shen, Minhao Cheng:
Towards Stable Backdoor Purification through Feature Shift Tuning. CoRR abs/2310.01875 (2023) - [i19]Mingyang Chen, Bo Huang, Junda Lu, Bing Li, Yi Wang, Minhao Cheng, Wei Wang:
Dataset Distillation via Adversarial Prediction Matching. CoRR abs/2312.08912 (2023) - 2022
- [j1]Chenxi Liu, Zhu Xiao, Dong Wang, Minhao Cheng, Hongyang Chen, Jiawei Cai:
Foreseeing private car transfer between urban regions with multiple graph-based generative adversarial networks. World Wide Web 25(6): 2515-2534 (2022) - [c22]Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You:
Concurrent Adversarial Learning for Large-Batch Training. ICLR 2022 - [c21]Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh:
CAT: Customized Adversarial Training for Improved Robustness. IJCAI 2022: 673-679 - [c20]Yong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You:
Random Sharpness-Aware Minimization. NeurIPS 2022 - [c19]Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh:
Efficient Non-Parametric Optimizer Search for Diverse Tasks. NeurIPS 2022 - [c18]Jaechul Roh, Minhao Cheng, Yajun Fang:
MSDT: Masked Language Model Scoring Defense in Text Domain. UV 2022: 1-5 - [i18]Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix Yu, Cho-Jui Hsieh:
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning. CoRR abs/2207.09653 (2022) - [i17]Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh:
Efficient Non-Parametric Optimizer Search for Diverse Tasks. CoRR abs/2209.13575 (2022) - [i16]Jaechul Roh, Minhao Cheng, Yajun Fang:
MSDT: Masked Language Model Scoring Defense in Text Domain. CoRR abs/2211.05371 (2022) - 2021
- [b1]Minhao Cheng:
On the Robustness of Neural Network: Attacks and Defenses. University of California, Los Angeles, USA, 2021 - [c17]Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das:
Self-Progressing Robust Training. AAAI 2021: 7107-7115 - [c16]Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. ICCV 2021: 10357-10366 - [c15]Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
DrNAS: Dirichlet Neural Architecture Search. ICLR 2021 - [c14]Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh:
Rethinking Architecture Selection in Differentiable NAS. ICLR 2021 - [i15]Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You:
Concurrent Adversarial Learning for Large-Batch Training. CoRR abs/2106.00221 (2021) - [i14]Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh:
Rethinking Architecture Selection in Differentiable NAS. CoRR abs/2108.04392 (2021) - [i13]Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. CoRR abs/2108.08019 (2021) - [i12]Yao Li, Minhao Cheng, Cho-Jui Hsieh, Thomas C. M. Lee:
A Review of Adversarial Attack and Defense for Classification Methods. CoRR abs/2111.09961 (2021) - 2020
- [c13]Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh:
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. AAAI 2020: 3601-3608 - [c12]Xiaoqing Zheng, Jiehang Zeng, Yi Zhou, Cho-Jui Hsieh, Minhao Cheng, Xuanjing Huang:
Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples. ACL 2020: 6600-6610 - [c11]Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh:
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. ICLR 2020 - [i11]Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh:
CAT: Customized Adversarial Training for Improved Robustness. CoRR abs/2002.06789 (2020) - [i10]Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
DrNAS: Dirichlet Neural Architecture Search. CoRR abs/2006.10355 (2020) - [i9]Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit S. Dhillon:
Voting based ensemble improves robustness of defensive models. CoRR abs/2011.14031 (2020) - [i8]Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das:
Self-Progressing Robust Training. CoRR abs/2012.11769 (2020)
2010 – 2019
- 2019
- [c10]Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh:
On the Robustness of Self-Attentive Models. ACL (1) 2019: 1520-1529 - [c9]Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. ICLR (Poster) 2019 - [c8]Minhao Cheng, Wei Wei, Cho-Jui Hsieh:
Evaluating and Enhancing the Robustness of Dialogue Systems: A Case Study on a Negotiation Agent. NAACL-HLT (1) 2019: 3325-3335 - [c7]Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander:
Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization. SDM 2019: 280-288 - [i7]Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh:
Natural Adversarial Sentence Generation with Gradient-based Perturbation. CoRR abs/1909.04495 (2019) - [i6]Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh:
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. CoRR abs/1909.10773 (2019) - [i5]Huan Zhang, Minhao Cheng, Cho-Jui Hsieh:
Enhancing Certifiable Robustness via a Deep Model Ensemble. CoRR abs/1910.14655 (2019) - 2018
- [c6]Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh:
Towards Robust Neural Networks via Random Self-ensemble. ECCV (7) 2018: 381-397 - [c5]Minhao Cheng, Ian Davidson, Cho-Jui Hsieh:
Extreme Learning to Rank via Low Rank Assumption. ICML 2018: 950-959 - [c4]Minhao Cheng, Cho-Jui Hsieh:
Distributed Primal-Dual Optimization for Non-uniformly Distributed Data. IJCAI 2018: 2028-2034 - [c3]Yao Li, Minhao Cheng, Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh:
Learning from Group Comparisons: Exploiting Higher Order Interactions. NeurIPS 2018: 4986-4995 - [i4]Minhao Cheng, Jinfeng Yi, Huan Zhang, Pin-Yu Chen, Cho-Jui Hsieh:
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. CoRR abs/1803.01128 (2018) - [i3]Liu Liu, Minhao Cheng, Cho-Jui Hsieh, Dacheng Tao:
Stochastic Zeroth-order Optimization via Variance Reduction method. CoRR abs/1805.11811 (2018) - [i2]Minhao Cheng, Thong Le, Pin-Yu Chen, Jinfeng Yi, Huan Zhang, Cho-Jui Hsieh:
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. CoRR abs/1807.04457 (2018) - 2017
- [c2]Huang Fang, Minhao Cheng, Cho-Jui Hsieh:
A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction. ICDM 2017: 101-110 - [i1]Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh:
Towards Robust Neural Networks via Random Self-ensemble. CoRR abs/1712.00673 (2017) - 2015
- [c1]Xinzheng Niu, Dazhuang Su, Minhao Cheng:
Intelligent Mobile Framework Based on Swarm Computation. CIT/IUCC/DASC/PICom 2015: 1000-1006
Coauthor Index
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