Jiao, Jiantao

42 publications

ICLR 2025 EmbedLLM: Learning Compact Representations of Large Language Models Richard Zhuang, Tianhao Wu, Zhaojin Wen, Andrew Li, Jiantao Jiao, Kannan Ramchandran

NeurIPS 2025 Generalization or Hallucination? Understanding Out-of-Context Reasoning in Transformers Yixiao Huang, Hanlin Zhu, Tianyu Guo, Jiantao Jiao, Somayeh Sojoudi, Michael I. Jordan, Stuart Russell, Song Mei

ICLR 2025 How to Evaluate Reward Models for RLHF Evan Frick, Tianle Li, Connor Chen, Wei-Lin Chiang, Anastasios Nikolas Angelopoulos, Jiantao Jiao, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica

NeurIPS 2025 Information-Driven Design of Imaging Systems Henry Pinkard, Leyla A Kabuli, Eric Markley, Tiffany Chien, Jiantao Jiao, Laura Waller

NeurIPS 2025 Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought Hanlin Zhu, Shibo Hao, Zhiting Hu, Jiantao Jiao, Stuart Russell, Yuandong Tian

ICML 2025 Thinking LLMs: General Instruction Following with Thought Generation Tianhao Wu, Janice Lan, Weizhe Yuan, Jiantao Jiao, Jason E Weston, Sainbayar Sukhbaatar

ICML 2025 Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning Dijia Su, Hanlin Zhu, Yingchen Xu, Jiantao Jiao, Yuandong Tian, Qinqing Zheng

NeurIPSW 2024 Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs Tianyu Guo, Druv Pai, Yu Bai, Jiantao Jiao, Michael Jordan, Song Mei

NeurIPS 2024 An Analysis of Tokenization: Transformers Under Markov Data Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran

ICML 2024 Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF Banghua Zhu, Michael Jordan, Jiantao Jiao

NeurIPS 2024 Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell

NeurIPS 2024 Toxicity Detection for Free Zhanhao Hu, Julien Piet, Geng Zhao, Jiantao Jiao, David Wagner

AISTATS 2023 Byzantine-Robust Federated Learning with Optimal Statistical Rates Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan

NeurIPS 2023 Doubly-Robust Self-Training Banghua Zhu, Mingyu Ding, Philip Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao

NeurIPS 2023 Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning Hanlin Zhu, Paria Rashidinejad, Jiantao Jiao

ICMLW 2023 Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning Hanlin Zhu, Paria Rashidinejad, Jiantao Jiao

ICML 2023 Jump-Start Reinforcement Learning Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman

NeurIPSW 2023 NexusRaven: A Commercially-Permissive Language Model for Function Calling Venkat Krishna Srinivasan, Zhen Dong, Banghua Zhu, Brian Yu, Damon Mosk-Aoyama, Kurt Keutzer, Jiantao Jiao, Jian Zhang

NeurIPSW 2023 NexusRaven: A Commercially-Permissive Language Model for Function Calling Venkat Krishna Srinivasan, Zhen Dong, Banghua Zhu, Brian Yu, Hanzi Mao, Damon Mosk-Aoyama, Kurt Keutzer, Jiantao Jiao, Jian Zhang

ICML 2023 Online Learning in Stackelberg Games with an Omniscient Follower Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael Jordan

ICLR 2023 Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao

NeurIPSW 2023 Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment Tianhao Wu, Banghua Zhu, Ruoyu Zhang, Zhaojin Wen, Kannan Ramchandran, Jiantao Jiao

ICLRW 2023 Principled Reinforcement Learning with Human Feedback from Pairwise or $k$-Wise Comparisons Banghua Zhu, Jiantao Jiao, Michael Jordan

ICMLW 2023 Principled Reinforcement Learning with Human Feedback from Pairwise or $k$-Wise Comparisons Banghua Zhu, Michael Jordan, Jiantao Jiao

ICML 2023 Principled Reinforcement Learning with Human Feedback from Pairwise or K-Wise Comparisons Banghua Zhu, Michael Jordan, Jiantao Jiao

AAAI 2023 Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning Jinhyun So, Ramy E. Ali, Basak Güler, Jiantao Jiao, Amir Salman Avestimehr

NeurIPS 2023 Towards Optimal Caching and Model Selection for Large Model Inference Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark Barrett, Michael I. Jordan, Jiantao Jiao

NeurIPSW 2023 Towards Optimal Statistical Watermarking Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason Lee, Jiantao Jiao, Michael Jordan

NeurIPS 2022 Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits Yifei Wang, Tavor Baharav, Yanjun Han, Jiantao Jiao, David Tse

JAIR 2022 Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma

NeurIPS 2022 Minimax Optimal Online Imitation Learning via Replay Estimation Gokul Swamy, Nived Rajaraman, Matt Peng, Sanjiban Choudhury, J. A. Bagnell, Steven Z. Wu, Jiantao Jiao, Kannan Ramchandran

ICML 2022 Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon Du, Jiantao Jiao

NeurIPS 2021 Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart J. Russell

NeurIPS 2021 MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E Gonzalez, Stuart J. Russell

NeurIPS 2021 On the Value of Interaction and Function Approximation in Imitation Learning Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran

NeurIPS 2020 SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory Paria Rashidinejad, Jiantao Jiao, Stuart J. Russell

NeurIPS 2020 Toward the Fundamental Limits of Imitation Learning Nived Rajaraman, Lin Yang, Jiantao Jiao, Kannan Ramchandran

JMLR 2019 Approximate Profile Maximum Likelihood Dmitri S. Pavlichin, Jiantao Jiao, Tsachy Weissman

ICML 2019 Theoretically Principled Trade-Off Between Robustness and Accuracy Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric Xing, Laurent El Ghaoui, Michael Jordan

NeurIPS 2018 Entropy Rate Estimation for Markov Chains with Large State Space Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu

COLT 2018 Local Moment Matching: A Unified Methodology for Symmetric Functional Estimation and Distribution Estimation Under Wasserstein Distance Yanjun Han, Jiantao Jiao, Tsachy Weissman

NeurIPS 2018 The Nearest Neighbor Information Estimator Is Adaptively near Minimax Rate-Optimal Jiantao Jiao, Weihao Gao, Yanjun Han