Intelligent Mobile Framework Based on Swarm Computation. - Xinzheng Niu; Dazhuang Su; Minhao Cheng (CIT/IUCC/DASC/PICom, 2015)

A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction. - Huang Fang; Minhao Cheng; Cho-Jui Hsieh (ICDM, 2017)

Towards Robust Neural Networks via Random Self-ensemble. - Xuanqing Liu; Minhao Cheng; Huan Zhang 001; Cho-Jui Hsieh (ECCV (7), 2018)

Extreme Learning to Rank via Low Rank Assumption. - Minhao Cheng; Ian Davidson; Cho-Jui Hsieh (ICML, 2018)

Distributed Primal-Dual Optimization for Non-uniformly Distributed Data. - Minhao Cheng; Cho-Jui Hsieh (IJCAI, 2018)

Learning from Group Comparisons: Exploiting Higher Order Interactions. - Yao Li 015; Minhao Cheng; Kevin Fujii; Fushing Hsieh; Cho-Jui Hsieh (NeurIPS, 2018)

Stochastic Zeroth-order Optimization via Variance Reduction method. - Liu Liu 014; Minhao Cheng; Cho-Jui Hsieh; Dacheng Tao (CoRR, 2018)

On the Robustness of Self-Attentive Models. - Yu-Lun Hsieh; Minhao Cheng; Da-Cheng Juan; Wei Wei 019; Wen-Lian Hsu; Cho-Jui Hsieh (ACL (1), 2019)

Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. - Minhao Cheng; Thong Le; Pin-Yu Chen; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh (ICLR (Poster), 2019)

Evaluating and Enhancing the Robustness of Dialogue Systems: A Case Study on a Negotiation Agent. - Minhao Cheng; Wei Wei 019; Cho-Jui Hsieh (NAACL-HLT (1), 2019)

Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization. - Huang Fang; Minhao Cheng; Cho-Jui Hsieh; Michael P. Friedlander (SDM, 2019)

Natural Adversarial Sentence Generation with Gradient-based Perturbation. - Yu-Lun Hsieh; Minhao Cheng; Da-Cheng Juan; Wei Wei 019; Wen-Lian Hsu; Cho-Jui Hsieh (CoRR, 2019)

Enhancing Certifiable Robustness via a Deep Model Ensemble. - Huan Zhang 001; Minhao Cheng; Cho-Jui Hsieh (CoRR, 2019)

Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. - Minhao Cheng; Jinfeng Yi; Pin-Yu Chen; Huan Zhang 001; Cho-Jui Hsieh (AAAI, 2020)

Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples. - Xiaoqing Zheng; Jiehang Zeng; Yi Zhou 018; Cho-Jui Hsieh; Minhao Cheng; Xuanjing Huang 001 (ACL, 2020)

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. - Minhao Cheng; Simranjit Singh 003; Patrick H. Chen; Pin-Yu Chen; Sijia Liu 001; Cho-Jui Hsieh (ICLR, 2020)

Voting based ensemble improves robustness of defensive models. - Devvrit; Minhao Cheng; Cho-Jui Hsieh; Inderjit S. Dhillon (CoRR, 2020)

Self-Progressing Robust Training. - Minhao Cheng; Pin-Yu Chen; Sijia Liu 001; Shiyu Chang; Cho-Jui Hsieh; Payel Das (AAAI, 2021)

RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. - Ruochen Wang; Xiangning Chen; Minhao Cheng; Xiaocheng Tang; Cho-Jui Hsieh (ICCV, 2021)

DrNAS: Dirichlet Neural Architecture Search. - Xiangning Chen; Ruochen Wang; Minhao Cheng; Xiaocheng Tang; Cho-Jui Hsieh (ICLR, 2021)

Rethinking Architecture Selection in Differentiable NAS. - Ruochen Wang; Minhao Cheng; Xiangning Chen; Xiaocheng Tang; Cho-Jui Hsieh (ICLR, 2021)

A Review of Adversarial Attack and Defense for Classification Methods. - Yao Li 015; Minhao Cheng; Cho-Jui Hsieh; Thomas C. M. Lee (CoRR, 2021)

On the Robustness of Neural Network: Attacks and Defenses. - Minhao Cheng (2021)

Concurrent Adversarial Learning for Large-Batch Training. - Yong Liu 020; Xiangning Chen; Minhao Cheng; Cho-Jui Hsieh; Yang You 001 (ICLR, 2022)

CAT: Customized Adversarial Training for Improved Robustness. - Minhao Cheng; Qi Lei; Pin-Yu Chen; Inderjit S. Dhillon; Cho-Jui Hsieh (IJCAI, 2022)

Random Sharpness-Aware Minimization. - Yong Liu 020; Siqi Mai; Minhao Cheng; Xiangning Chen; Cho-Jui Hsieh; Yang You 001 (NeurIPS, 2022)

Efficient Non-Parametric Optimizer Search for Diverse Tasks. - Ruochen Wang; Yuanhao Xiong; Minhao Cheng; Cho-Jui Hsieh (NeurIPS, 2022)

MSDT: Masked Language Model Scoring Defense in Text Domain. - Jaechul Roh; Minhao Cheng; Yajun Fang (UV, 2022)

Foreseeing private car transfer between urban regions with multiple graph-based generative adversarial networks. - Chenxi Liu 003; Zhu Xiao; Dong Wang 016; Minhao Cheng; Hongyang Chen; Jiawei Cai (World Wide Web, 2022)

Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation. - Bo Huang; Mingyang Chen; Yi Wang 017; Junda Lu 001; Minhao Cheng; Wei Wang 011 (CVPR, 2023)

FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning. - Yuanhao Xiong; Ruochen Wang; Minhao Cheng; Felix X. Yu; Cho-Jui Hsieh (CVPR, 2023)

PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. - Lichang Chen; Jiuhai Chen; Heng Huang; Minhao Cheng (EMNLP, 2023)

Identification of the Adversary from a Single Adversarial Example. - Minhao Cheng; Rui Min; Haochen Sun 001; Pin-Yu Chen (ICML, 2023)

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. - Zeyu Qin; Liuyi Yao; Daoyuan Chen; Yaliang Li; Bolin Ding; Minhao Cheng (KDD, 2023)

Towards Stable Backdoor Purification through Feature Shift Tuning. - Rui Min; Zeyu Qin; Li Shen 008; Minhao Cheng (NeurIPS, 2023)

PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. - Lichang Chen; Heng Huang; Minhao Cheng (CoRR, 2023)

Backdoor Learning on Sequence to Sequence Models. - Lichang Chen; Minhao Cheng; Heng Huang (CoRR, 2023)

Backdoor Attack against Object Detection with Clean Annotation. - Yize Cheng; Wenbin Hu 002; Minhao Cheng (CoRR, 2023)

Dataset Distillation via Adversarial Prediction Matching. - Mingyang Chen; Bo Huang; Junda Lu 001; Bing Li 002; Yi Wang 017; Minhao Cheng; Wei Wang 011 (CoRR, 2023)

CurvAGN: Curvature-based Adaptive Graph Neural Networks for Predicting Protein-Ligand Binding Affinity. - Jianqiu Wu; Hongyang Chen; Minhao Cheng; Haoyi Xiong (BMC Bioinform., 2023)

Exploring Robustness of GNN against Universal Injection Attack from a Worst-case Perspective. - Dandan Ni; Sheng Zhang 006; Cong Deng; Han Liu 008; Gang Chen 001; Minhao Cheng; Hongyang Chen (CIKM, 2024)

Understanding the Impact of Negative Prompts: When and How Do They Take Effect? - Yuanhao Ban; Ruochen Wang; Tianyi Zhou 001; Minhao Cheng; Boqing Gong; Cho-Jui Hsieh (ECCV (89), 2024)

A Watermark-Conditioned Diffusion Model for IP Protection. - Rui Min; Sen Li; Hongyang Chen; Minhao Cheng (ECCV (69), 2024)

Where Am I From? Identifying Origin of LLM-generated Content. - Liying Li; Yihan Bai; Minhao Cheng (EMNLP, 2024)

DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers. - Xirui Li; Ruochen Wang; Minhao Cheng; Tianyi Zhou 001; Cho-Jui Hsieh (EMNLP (Findings), 2024)

GuardEmb: Dynamic Watermark for Safeguarding Large Language Model Embedding Service Against Model Stealing Attack. - Liaoyaqi Wang; Minhao Cheng (EMNLP (Findings), 2024)

Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective. - Kuan Li; Yiwen Chen; Yang Liu 200; Jin Wang 007; Qing He 003; Minhao Cheng; Xiang Ao 001 (ICLR, 2024)

One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. - Ruochen Wang; Sohyun An; Minhao Cheng; Tianyi Zhou 001; Sung Ju Hwang; Cho-Jui Hsieh (ICML, 2024)

Unsupervised Heterogeneous Graph Rewriting Attack via Node Clustering. - Haosen Wang; Can Xu; Chenglong Shi; Pengfei Zheng; Shiming Zhang; Minhao Cheng; Hongyang Chen (KDD, 2024)

Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. - Rui Min; Zeyu Qin; Nevin L. Zhang; Li Shen 008; Minhao Cheng (NeurIPS, 2024)

MuLan: Multimodal-LLM Agent for Progressive Multi-Object Diffusion. - Sen Li; Ruochen Wang; Cho-Jui Hsieh; Minhao Cheng; Tianyi Zhou 001 (CoRR, 2024)

Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning. - Yong Liu 020; Zirui Zhu; Chaoyu Gong; Minhao Cheng; Cho-Jui Hsieh; Yang You 001 (CoRR, 2024)

DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers. - Xirui Li; Ruochen Wang; Minhao Cheng; Tianyi Zhou 001; Cho-Jui Hsieh (CoRR, 2024)

Input Snapshots Fusion for Scalable Discrete Dynamic Graph Nerual Networks. - QingGuo Qi; Hongyang Chen; Minhao Cheng; Han Liu 008 (CoRR, 2024)

Invisible Backdoor Attacks on Diffusion Models. - Sen Li; Junchi Ma; Minhao Cheng (CoRR, 2024)

MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries? - Xirui Li; Hengguang Zhou; Ruochen Wang; Tianyi Zhou 001; Minhao Cheng; Cho-Jui Hsieh (CoRR, 2024)

Defense Against Syntactic Textual Backdoor Attacks with Token Substitution. - Xinglin Li; Xianwen He; Yao Li 015; Minhao Cheng (CoRR, 2024)

Trusted Aggregation (TAG): Backdoor Defense in Federated Learning. - Joseph Lavond; Minhao Cheng; Yao Li 015 (Trans. Mach. Learn. Res., 2024)

CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP. - Tianyu Yang; Lisen Dai; Xiangqi Wang; Minhao Cheng; Yapeng Tian; Xiangliang Zhang 001 (ACL (1), 2025)

The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise. - Yuanhao Ban; Ruochen Wang; Tianyi Zhou 001; Boqing Gong; Cho-Jui Hsieh; Minhao Cheng (ICLR, 2025)

Is Your Multimodal Language Model Oversensitive to Safe Queries? - Xirui Li; Hengguang Zhou; Ruochen Wang; Tianyi Zhou 001; Minhao Cheng; Cho-Jui Hsieh (ICLR, 2025)

Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks. - QingGuo Qi; Hongyang Chen; Minhao Cheng; Han Liu 008 (KDD (1), 2025)

Improving Your Model Ranking on Chatbot Arena by Vote Rigging. - Rui Min; Tianyu Pang; Chao Du; Qian Liu 012; Minhao Cheng; Min Lin (CoRR, 2025)

Leveraging Reasoning with Guidelines to Elicit and Utilize Knowledge for Enhancing Safety Alignment. - Haoyu Wang 003; Zeyu Qin; Li Shen 008; Xueqian Wang 001; Minhao Cheng; Dacheng Tao (CoRR, 2025)

LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs - No Silver Bullet for LC or RAG Routing. - Kuan Li; Liwen Zhang; Yong Jiang 005; Pengjun Xie; Fei Huang 002; Shuai Wang; Minhao Cheng (CoRR, 2025)

R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model. - Hengguang Zhou; Xirui Li; Ruochen Wang; Minhao Cheng; Tianyi Zhou 001; Cho-Jui Hsieh (CoRR, 2025)

Scaling Laws of Synthetic Data for Language Models. - Zeyu Qin; Qingxiu Dong; Xingxing Zhang 002; Li Dong 004; Xiaolong Huang; Ziyi Yang; Mahmoud Khademi; Dongdong Zhang 001; Hany Hassan Awadalla; Yi R. Fung 001; Weizhu Chen; Minhao Cheng; et al. (CoRR, 2025)

Exploring Expert Failures Improves LLM Agent Tuning. - Li-Cheng Lan; Andrew Bai; Minhao Cheng; Cho-Jui Hsieh; Tianyi Zhou 001 (CoRR, 2025)

Optimizing Token Choice for Code Watermarking: A RL Approach. - Zhimeng Guo; Huaisheng Zhu; Siyuan Xu; Hangfan Zhang; Teng Xiao; Minhao Cheng (CoRR, 2025)