| 2026 | ACL | Empowering Reliable Visual-Centric Instruction Following in MLLMs. | Weilei He, Feng Ju, Zhiyuan Fan, Rui Min, Minhao Cheng |
| 2026 | ACL | A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning. | Tianyu Yang, Sihong Wu, Yilun Zhao, Zhenwen Liang, Lisen Dai, Chen Zhao, Minhao Cheng, Arman Cohan, Xiangliang Zhang |
| 2025 | ACL | CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP. | Tianyu Yang, Lisen Dai, Xiangqi Wang, Minhao Cheng, Yapeng Tian, Xiangliang Zhang |
| 2025 | ICLR | The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise. | Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-Jui Hsieh, Minhao Cheng |
| 2025 | ICLR | Is Your Multimodal Language Model Oversensitive to Safe Queries? | Xirui Li, Hengguang Zhou, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh |
| 2025 | ICML | SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning. | Yong Liu, Di Fu, Shenggan Cheng, Zirui Zhu, Yang Luo, Minhao Cheng, Cho-Jui Hsieh, Yang You |
| 2025 | ICML | LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs - No Silver Bullet for LC or RAG Routing. | Kuan Li, Liwen Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Shuai Wang, Minhao Cheng |
| 2025 | ICML | Improving Your Model Ranking on Chatbot Arena by Vote Rigging. | Rui Min, Tianyu Pang, Chao Du, Qian Liu, Minhao Cheng, Min Lin |
| 2025 | ICML | Safety Reasoning with Guidelines. | Haoyu Wang, Zeyu Qin, Li Shen, Xueqian Wang, Dacheng Tao, Minhao Cheng |
| 2025 | KDD | Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks. | QingGuo Qi, Hongyang Chen, Minhao Cheng, Han Liu |
| 2024 | CIKM | Exploring Robustness of GNN against Universal Injection Attack from a Worst-case Perspective. | Dandan Ni, Sheng Zhang, Cong Deng, Han Liu, Gang Chen, Minhao Cheng, Hongyang Chen |
| 2024 | ECCV | Understanding the Impact of Negative Prompts: When and How Do They Take Effect? | Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Boqing Gong, Cho-Jui Hsieh |
| 2024 | ECCV | A Watermark-Conditioned Diffusion Model for IP Protection. | Rui Min, Sen Li, Hongyang Chen, Minhao Cheng |
| 2024 | EMNLP | Where Am I From? Identifying Origin of LLM-generated Content. | Liying Li, Yihan Bai, Minhao Cheng |
| 2024 | EMNLP | DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers. | Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh |
| 2024 | EMNLP | GuardEmb: Dynamic Watermark for Safeguarding Large Language Model Embedding Service Against Model Stealing Attack. | Liaoyaqi Wang, Minhao Cheng |
| 2024 | ICLR | Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective. | Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng, Xiang Ao |
| 2024 | ICML | One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. | Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh |
| 2024 | KDD | Unsupervised Heterogeneous Graph Rewriting Attack via Node Clustering. | Haosen Wang, Can Xu, Chenglong Shi, Pengfei Zheng, Shiming Zhang, Minhao Cheng, Hongyang Chen |
| 2023 | CVPR | Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation. | Bo Huang, Mingyang Chen, Yi Wang, Junda Lu, Minhao Cheng, Wei Wang |
| 2023 | CVPR | FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning. | Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix X. Yu, Cho-Jui Hsieh |
| 2023 | EMNLP | PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. | Lichang Chen, Jiuhai Chen, Heng Huang, Minhao Cheng |
| 2023 | ICML | Identification of the Adversary from a Single Adversarial Example. | Minhao Cheng, Rui Min, Haochen Sun, Pin-Yu Chen |
| 2023 | KDD | Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. | Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng |
| 2022 | ICLR | Concurrent Adversarial Learning for Large-Batch Training. | Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You |
| 2022 | IJCAI | CAT: Customized Adversarial Training for Improved Robustness. | Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh |
| 2021 | AAAI | Self-Progressing Robust Training. | Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das |
| 2021 | ICCV | RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. | Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh |
| 2021 | ICLR | DrNAS: Dirichlet Neural Architecture Search. | Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh |
| 2021 | ICLR | Rethinking Architecture Selection in Differentiable NAS. | Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh |
| 2020 | AAAI | Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. | Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh |
| 2020 | ACL | Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples. | Xiaoqing Zheng, Jiehang Zeng, Yi Zhou, Cho-Jui Hsieh, Minhao Cheng, Xuanjing Huang |
| 2020 | ICLR | Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. | Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh |
| 2019 | ACL | On the Robustness of Self-Attentive Models. | Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh |
| 2019 | ICLR | Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. | Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh |
| 2019 | NAACL | Evaluating and Enhancing the Robustness of Dialogue Systems: A Case Study on a Negotiation Agent. | Minhao Cheng, Wei Wei, Cho-Jui Hsieh |
| 2019 | SDM | Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization. | Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander |
| 2018 | ECCV | Towards Robust Neural Networks via Random Self-ensemble. | Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh |
| 2018 | ICML | Extreme Learning to Rank via Low Rank Assumption. | Minhao Cheng, Ian Davidson, Cho-Jui Hsieh |
| 2018 | IJCAI | Distributed Primal-Dual Optimization for Non-uniformly Distributed Data. | Minhao Cheng, Cho-Jui Hsieh |
| 2017 | ICDM | A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction. | Huang Fang, Minhao Cheng, Cho-Jui Hsieh |