| 2025 | ACL | Synergistic Weak-Strong Collaboration by Aligning Preferences. | Yizhu Jiao, Xuchao Zhang, Zhaoyang Wang, Yubo Ma, Zhun Deng, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Jiawei Han, Huaxiu Yao |
| 2025 | ICML | Conformal Tail Risk Control for Large Language Model Alignment. | Catherine Yu-Chi Chen, Jingyan Shen, Zhun Deng, Lihua Lei |
| 2025 | ICML | QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions. | Zhun Deng, Thomas P. Zollo, Benjamin Eyre, Amogh Inamdar, David Madras, Richard S. Zemel |
| 2024 | ICLR | Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. | Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao |
| 2024 | ICLR | Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models. | Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard S. Zemel |
| 2024 | ICML | Learning and Forgetting Unsafe Examples in Large Language Models. | Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren |
| 2023 | AISTATS | Reinforcement Learning with Stepwise Fairness Constraints. | Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes |
| 2023 | AISTATS | Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. | Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang |
| 2023 | ICLR | FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. | Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou |
| 2023 | ICLR | Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions. | Jake Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard S. Zemel |
| 2023 | ICML | How Does Information Bottleneck Help Deep Learning? | Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang |
| 2022 | ICLR | An Unconstrained Layer-Peeled Perspective on Neural Collapse. | Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su |
| 2022 | ICML | Robustness Implies Generalization via Data-Dependent Generalization Bounds. | Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang |
| 2022 | ICML | When and How Mixup Improves Calibration. | Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou |
| 2021 | AISTATS | Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. | Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou |
| 2021 | ICLR | How Does Mixup Help With Robustness and Generalization? | Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou |
| 2021 | ICML | Toward Better Generalization Bounds with Locally Elastic Stability. | Zhun Deng, Hangfeng He, Weijie J. Su |
| 2020 | ICML | Interpreting Robust Optimization via Adversarial Influence Functions. | Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang |
| 2020 | ICML | Towards Understanding the Dynamics of the First-Order Adversaries. | Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su |
| 2017 | ISIT | The number of independent sets in hexagonal graphs. | Zhun Deng, Jie Ding, Kathryn Heal, Vahid Tarokh |