Deng, Zhun

29 publications

ICML 2025 Conformal Tail Risk Control for Large Language Model Alignment Catherine Chen, Jingyan Shen, Zhun Deng, Lihua Lei

NeurIPS 2025 Performative Risk Control: Calibrating Models for Reliable Deployment Under Performativity Victor Li, Baiting Chen, Yuzhen Mao, Qi Lei, Zhun Deng

ICML 2025 QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions Zhun Deng, Thomas P Zollo, Benjamin Eyre, Amogh Inamdar, David Madras, Richard Zemel

TMLR 2025 Reliable and Responsible Foundation Models Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, Rene Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao

NeurIPS 2025 Statistical Inference Under Performativity Xiang Li, Yunai Li, Huiying Zhong, Lihua Lei, Zhun Deng

ICLR 2024 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

TMLR 2024 Improving Predictor Reliability with Selective Recalibration Thomas P Zollo, Zhun Deng, Jake Snell, Toniann Pitassi, Richard Zemel

ICML 2024 Learning and Forgetting Unsafe Examples in Large Language Models Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren

ICLR 2024 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 Zemel

NeurIPSW 2024 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

NeurIPSW 2023 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

NeurIPS 2023 Distribution-Free Statistical Dispersion Control for Societal Applications Zhun Deng, Thomas Zollo, Jake Snell, Toniann Pitassi, Richard S. Zemel

ICLR 2023 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

ICML 2023 How Does Information Bottleneck Help Deep Learning? Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang

NeurIPS 2023 PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos Psaros, Kenji Kawaguchi

NeurIPSW 2023 Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models Thomas Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard Zemel

ICLR 2023 Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions Jake Snell, Thomas P Zollo, Zhun Deng, Toniann Pitassi, Richard Zemel

AISTATS 2023 Reinforcement Learning with Stepwise Fairness Constraints Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David Parkes

JMLR 2023 The Power of Contrast for Feature Learning: A Theoretical Analysis Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang

AISTATS 2023 Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang

ICLR 2022 An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J Su

ICML 2022 Robustness Implies Generalization via Data-Dependent Generalization Bounds Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang

ICML 2022 When and How Mixup Improves Calibration Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou

AISTATS 2021 Improving Adversarial Robustness via Unlabeled Out-of-Domain Data Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou

NeurIPS 2021 Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y Zou

ICLR 2021 How Does Mixup Help with Robustness and Generalization? Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou

ICML 2021 Toward Better Generalization Bounds with Locally Elastic Stability Zhun Deng, Hangfeng He, Weijie Su

ICML 2020 Interpreting Robust Optimization via Adversarial Influence Functions Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang

ICML 2020 Towards Understanding the Dynamics of the First-Order Adversaries Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie Su