Zhang, Linjun

40 publications

ICLR 2026 MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning Peng Xia, Jinglu Wang, Yibo Peng, Kaide Zeng, Zihan Dong, Xian Wu, Xiangru Tang, Hongtu Zhu, Yun Li, Linjun Zhang, Shujie Liu, Yan Lu, Huaxiu Yao

ICLR 2026 Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards Shirley Wu, Parth Sarthi, Shiyu Zhao, Aaron Lee, Herumb Shandilya, Adrian Mladenic Grobelnik, Nurendra Choudhary, Edward W Huang, Karthik Subbian, Linjun Zhang, Diyi Yang, James Zou, Jure Leskovec

ICLR 2026 Residual Feature Integration Is Sufficient to Prevent Negative Transfer Yichen Xu, Ryumei Nakada, Linjun Zhang, Lexin Li

ICLR 2026 Secret-Protected Evolution for Differentially Private Synthetic Text Generation Tianze Wang, Zhaoyu Chen, Jian Du, Yingtai Xiao, Linjun Zhang, Qiang Yan

NeurIPS 2025 AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play Ran Xu, Yuchen Zhuang, Zihan Dong, Ruiyu Wang, Yue Yu, Joyce C. Ho, Linjun Zhang, Haoyu Wang, Wenqi Shi, Carl Yang

ICML 2025 FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees Fan Nie, Xiaotian Hou, Shuhang Lin, James Zou, Huaxiu Yao, Linjun Zhang

ICLR 2025 MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao

ICML 2025 MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment Tianze Wang, Dongnan Gui, Yifan Hu, Shuhang Lin, Linjun Zhang

ICML 2025 Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Tianci Liu, Ruirui Li, Zihan Dong, Hui Liu, Xianfeng Tang, Qingyu Yin, Linjun Zhang, Haoyu Wang, Jing Gao

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

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

NeurIPS 2024 Calibrated Self-Rewarding Vision Language Models Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao

ICMLW 2024 Calibrated Self-Rewarding Vision Language Models Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao

ICML 2024 Conformal Prediction for Deep Classifier via Label Ranking Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei

ICML 2024 Fair Risk Control: A Generalized Framework for Calibrating Multi-Group Fairness Risks Lujing Zhang, Aaron Roth, Linjun Zhang

NeurIPSW 2024 MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Linjun Zhang, James Zou, Huaxiu Yao

NeurIPSW 2024 MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao

NeurIPS 2024 Order-Independence Without Fine Tuning Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork

NeurIPS 2024 S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-Tuning by Structured Sparsity Xinyu Yang, Jixuan Leng, Geyang Guo, Jiawei Zhao, Ryumei Nakada, Linjun Zhang, Huaxiu Yao, Beidi Chen

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 Beyond Confidence: Reliable Models Should Also Consider Atypicality Mert Yuksekgonul, Linjun Zhang, James Y Zou, Carlos Guestrin

ICMLW 2023 Beyond Confidence: Reliable Models Should Also Consider Atypicality Mert Yuksekgonul, Linjun Zhang, James Zou, Carlos Guestrin

ICLRW 2023 Beyond Confidence: Reliable Models Should Also Quantify Atypicality Mert Yuksekgonul, Linjun Zhang, James Zou, Carlos Guestrin

ICML 2023 Discover and Cure: Concept-Aware Mitigation of Spurious Correlation Shirley Wu, Mert Yuksekgonul, Linjun Zhang, James Zou

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

ICLR 2023 FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee Puheng Li, James Zou, Linjun Zhang

AISTATS 2023 Freeze Then Train: Towards Provable Representation Learning Under Spurious Correlations and Feature Noise Haotian Ye, James Zou, Linjun Zhang

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

NeurIPS 2022 C-Mixup: Improving Generalization in Regression Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y Zou, Chelsea Finn

ICML 2022 Improving Out-of-Distribution Robustness via Selective Augmentation Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn

ICLR 2022 Meta-Learning with Fewer Tasks Through Task Interpolation Huaxiu Yao, Linjun Zhang, Chelsea Finn

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 A Central Limit Theorem for Differentially Private Query Answering Jinshuo Dong, Weijie Su, Linjun Zhang

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 Improving Generalization in Meta-Learning via Task Augmentation Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui () Li

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