Zhun Deng - RankMe

71 papers A* 18A 4B 1Journal 45Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency. CoRR Zhangyi Liu, Huaizhi Qu, Xiaowei Yin, He Sun, Yanjun Han, Tianlong Chen, Zhun Deng
2026	J	`jnl`	Recommending Best Paper Awards for ML/AI Conferences via the Isotonic Mechanism. CoRR Garrett G. Wen, Buxin Su, Natalie Collina, Zhun Deng, Weijie J. Su
2026	J	`jnl`	Reliable and Responsible Foundation Models: A Comprehensive Survey. CoRR 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 Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2026	J	`jnl`	Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges. CoRR Ruomeng Ding, Yifei Pang, He Sun, Yizhong Wang, Zhiwei Steven Wu, Zhun Deng
2026	J	`jnl`	Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions. CoRR Ruomeng Ding, Tianwei Gao, Thomas P. Zollo, Eitan Bachmat, Richard S. Zemel, Zhun Deng
2025	A*	`conf`	Conformal Tail Risk Control for Large Language Model Alignment. ICML Catherine Yu-Chi Chen, Jingyan Shen, Zhun Deng, Lihua Lei
2025	J	`jnl`	Conformal Tail Risk Control for Large Language Model Alignment. CoRR Catherine Yu-Chi Chen, Jingyan Shen, Zhun Deng, Lihua Lei
2025	J	`jnl`	Performative Risk Control: Calibrating Models for Reliable Deployment under Performativity. CoRR Victor Li, Baiting Chen, Yuzhen Mao, Qi Lei, Zhun Deng
2025	A*	`conf`	QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions. ICML Zhun Deng, Thomas P. Zollo, Benjamin Eyre, Amogh Inamdar, David Madras, Richard S. Zemel
2025	J	`jnl`	QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions. CoRR Zhun Deng, Thomas P. Zollo, Benjamin Eyre, Amogh Inamdar, David Madras, Richard S. Zemel
2025	J	`jnl`	Reliable and Responsible Foundation Models. Trans. Mach. Learn. Res. 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 J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025	J	`jnl`	Statistical Inference under Performativity. CoRR Xiang Li, Yunai Li, Huiying Zhong, Lihua Lei, Zhun Deng
2025	—	`conf`	Synergistic Weak-Strong Collaboration by Aligning Preferences. ACL (1) Yizhu Jiao, Xuchao Zhang, Zhaoyang Wang, Yubo Ma, Zhun Deng, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Jiawei Han, Huaxiu Yao
2025	J	`jnl`	Synergistic Weak-Strong Collaboration by Aligning Preferences. CoRR Yizhu Jiao, Xuchao Zhang, Zhaoyang Wang, Yubo Ma, Zhun Deng, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Jiawei Han, Huaxiu Yao
2024	J	`jnl`	An Economic Solution to Copyright Challenges of Generative AI. CoRR Jiachen T. Wang, Zhun Deng, Hiroaki Chiba-Okabe, Boaz Barak, Weijie J. Su
2024	A*	`conf`	Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
2024	J	`jnl`	Can AI Be as Creative as Humans? CoRR Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
2024	J	`jnl`	Improving Predictor Reliability with Selective Recalibration. CoRR Thomas P. Zollo, Zhun Deng, Jake C. Snell, Toniann Pitassi, Richard S. Zemel
2024	J	`jnl`	Improving Predictor Reliability with Selective Recalibration. Trans. Mach. Learn. Res. Thomas P. Zollo, Zhun Deng, Jake Snell, Toniann Pitassi, Richard S. Zemel
2024	A*	`conf`	Learning and Forgetting Unsafe Examples in Large Language Models. ICML Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren
2024	A*	`conf`	Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models. ICLR Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard S. Zemel
2024	J	`jnl`	Provable Multi-Party Reinforcement Learning with Diverse Human Feedback. CoRR Huiying Zhong, Zhun Deng, Weijie J. Su, Zhiwei Steven Wu, Linjun Zhang
2023	J	`jnl`	Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
2023	—	`conf`	Decision-Aware Conditional GANs for Time Series Data. ICAIF He Sun, Zhun Deng, Hui Chen, David C. Parkes
2023	A*	`conf`	Distribution-Free Statistical Dispersion Control for Societal Applications. NeurIPS Zhun Deng, Thomas P. Zollo, Jake Snell, Toniann Pitassi, Richard S. Zemel
2023	J	`jnl`	Distribution-Free Statistical Dispersion Control for Societal Applications. CoRR Zhun Deng, Thomas P. Zollo, Jake C. Snell, Toniann Pitassi, Richard S. Zemel
2023	A*	`conf`	FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
2023	A	`conf`	HappyMap : A Generalized Multicalibration Method. ITCS Zhun Deng, Cynthia Dwork, Linjun Zhang
2023	J	`jnl`	HappyMap: A Generalized Multi-calibration Method. CoRR Zhun Deng, Cynthia Dwork, Linjun Zhang
2023	A*	`conf`	How Does Information Bottleneck Help Deep Learning? ICML Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang
2023	J	`jnl`	How Does Information Bottleneck Help Deep Learning? CoRR Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang
2023	J	`jnl`	Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou
2023	J	`jnl`	Learning and Forgetting Unsafe Examples in Large Language Models. CoRR Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren
2023	A*	`conf`	PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. NeurIPS Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi
2023	J	`jnl`	PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. CoRR Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi
2023	J	`jnl`	Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models. CoRR Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake C. Snell, Toniann Pitassi, Richard S. Zemel
2023	A*	`conf`	Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions. ICLR Jake Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard S. Zemel
2023	A	`conf`	Reinforcement Learning with Stepwise Fairness Constraints. AISTATS Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes
2023	J	`jnl`	The Power of Contrast for Feature Learning: A Theoretical Analysis. J. Mach. Learn. Res. Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
2023	A	`conf`	Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
2023	J	`jnl`	Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
2022	A*	`conf`	An Unconstrained Layer-Peeled Perspective on Neural Collapse. ICLR Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su
2022	J	`jnl`	FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. CoRR Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
2022	J	`jnl`	Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach. CoRR Jiayao Zhang, Hongming Zhang, Zhun Deng, Dan Roth
2022	J	`jnl`	Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions. CoRR Jake C. Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard S. Zemel
2022	J	`jnl`	Reinforcement Learning with Stepwise Fairness Constraints. CoRR Zhun Deng, He Sun, Zhiwei Steven Wu, Linjun Zhang, David C. Parkes
2022	A*	`conf`	Robustness Implies Generalization via Data-Dependent Generalization Bounds. ICML Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang
2022	J	`jnl`	Robustness Implies Generalization via Data-Dependent Generalization Bounds. CoRR Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang
2022	J	`jnl`	Understanding Dynamics of Nonlinear Representation Learning and Its Application. Neural Comput. Kenji Kawaguchi, Linjun Zhang, Zhun Deng
2022	A*	`conf`	When and How Mixup Improves Calibration. ICML Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
2021	A*	`conf`	Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou
2021	J	`jnl`	Adversarial Training Helps Transfer Learning via Better Representations. CoRR Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou
2021	J	`jnl`	An Unconstrained Layer-Peeled Perspective on Neural Collapse. CoRR Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su
2021	A*	`conf`	How Does Mixup Help With Robustness and Generalization? ICLR Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou
2021	—	`conf`	How Shrinking Gradient Noise Helps the Performance of Neural Networks. IEEE BigData Zhun Deng, Jiaoyang Huang, Kenji Kawaguchi
2021	A	`conf`	Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou
2021	J	`jnl`	Scaffolding Sets. CoRR Maya Burhanpurkar, Zhun Deng, Cynthia Dwork, Linjun Zhang
2021	J	`jnl`	The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
2021	A*	`conf`	Toward Better Generalization Bounds with Locally Elastic Stability. ICML Zhun Deng, Hangfeng He, Weijie J. Su
2021	J	`jnl`	Understanding Dynamics of Nonlinear Representation Learning and Its Application. CoRR Kenji Kawaguchi, Linjun Zhang, Zhun Deng
2021	J	`jnl`	When and How Mixup Improves Calibration. CoRR Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
2020	J	`jnl`	Decision-Aware Conditional GANs for Time Series Data. CoRR He Sun, Zhun Deng, Hui Chen, David C. Parkes
2020	J	`jnl`	How Does Mixup Help With Robustness and Generalization? CoRR Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou
2020	J	`jnl`	Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou
2020	A*	`conf`	Interpreting Robust Optimization via Adversarial Influence Functions. ICML Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
2020	J	`jnl`	Interpreting Robust Optimization via Adversarial Influence Functions. CoRR Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
2020	J	`jnl`	Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations. CoRR Zhun Deng, Frances Ding, Cynthia Dwork, Rachel Hong, Giovanni Parmigiani, Prasad Patil, Pragya Sur
2020	J	`jnl`	Toward Better Generalization Bounds with Locally Elastic Stability. CoRR Zhun Deng, Hangfeng He, Weijie J. Su
2020	A*	`conf`	Towards Understanding the Dynamics of the First-Order Adversaries. ICML Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su
2020	J	`jnl`	Towards Understanding the Dynamics of the First-Order Adversaries. CoRR Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su
2017	B	`conf`	The number of independent sets in hexagonal graphs. ISIT Zhun Deng, Jie Ding, Kathryn Heal, Vahid Tarokh