| 2025 | EMNLP | Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge. | Tianhao Wu, Weizhe Yuan, Olga Golovneva, Jing Xu, Yuandong Tian, Jiantao Jiao, Jason E. Weston, Sainbayar Sukhbaatar |
| 2025 | ICLR | 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 |
| 2025 | ICLR | EmbedLLM: Learning Compact Representations of Large Language Models. | Richard Zhuang, Tianhao Wu, Zhaojin Wen, Andrew Li, Jiantao Jiao, Kannan Ramchandran |
| 2025 | ICML | Thinking LLMs: General Instruction Following with Thought Generation. | Tianhao Wu, Janice Lan, Weizhe Yuan, Jiantao Jiao, Jason E. Weston, Sainbayar Sukhbaatar |
| 2025 | ICML | Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning. | DiJia Su, Hanlin Zhu, Yingchen Xu, Jiantao Jiao, Yuandong Tian, Qinqing Zheng |
| 2024 | ICML | Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. | Banghua Zhu, Michael I. Jordan, Jiantao Jiao |
| 2024 | ICRA | Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration. | Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, Wei Zhan |
| 2023 | AAAI | Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. | Jinhyun So, Ramy E. Ali, Basak Gler, Jiantao Jiao, Amir Salman Avestimehr |
| 2023 | AISTATS | Byzantine-Robust Federated Learning with Optimal Statistical Rates. | Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan |
| 2023 | ICLR | Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. | Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao |
| 2023 | ICML | Jump-Start Reinforcement Learning. | Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Josphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman |
| 2023 | ICML | Online Learning in Stackelberg Games with an Omniscient Follower. | Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan |
| 2023 | ICML | Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. | Banghua Zhu, Michael I. Jordan, Jiantao Jiao |
| 2023 | ISIT | On the Optimal Bounds for Noisy Computing. | Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang |
| 2022 | ICML | Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. | Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao |
| 2022 | ISIT | Robust Estimation for Non-parametric Families via Generative Adversarial Networks. | Banghua Zhu, Jiantao Jiao, Michael I. Jordan |
| 2020 | ISIT | When does the Tukey Median work? | Banghua Zhu, Jiantao Jiao, Jacob Steinhardt |
| 2019 | ICML | Theoretically Principled Trade-off between Robustness and Accuracy. | Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan |
| 2019 | MOBIHOC | Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains. | Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath |
| 2018 | COLT | Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance. | Yanjun Han, Jiantao Jiao, Tsachy Weissman |
| 2018 | ISIT | Minimax Redundancy for Markov Chains with Large State Space. | Kedar Tatwawadi, Jiantao Jiao, Tsachy Weissman |
| 2017 | ISIT | Dependence measures bounding the exploration bias for general measurements. | Jiantao Jiao, Yanjun Han, Tsachy Weissman |
| 2016 | ACSSC | Beyond maximum likelihood: Boosting the Chow-Liu algorithm for large alphabets. | Jiantao Jiao, Yanjun Han, Tsachy Weissman |
| 2016 | ISIT | Minimax estimation of the L1 distance. | Jiantao Jiao, Yanjun Han, Tsachy Weissman |
| 2016 | ISIT | Mutual information, relative entropy and estimation error in semi-martingale channels. | Jiantao Jiao, Kartik Venkat, Tsachy Weissman |
| 2016 | ISITA | Minimax rate-optimal estimation of KL divergence between discrete distributions. | Yanjun Han, Jiantao Jiao, Tsachy Weissman |
| 2015 | ISIT | Does dirichlet prior smoothing solve the Shannon entropy estimation problem? | Yanjun Han, Jiantao Jiao, Tsachy Weissman |
| 2015 | ISIT | Adaptive estimation of Shannon entropy. | Yanjun Han, Jiantao Jiao, Tsachy Weissman |
| 2015 | ISIT | Minimax estimation of discrete distributions. | Yanjun Han, Jiantao Jiao, Tsachy Weissman |
| 2015 | ISIT | Maximum Likelihood Estimation of information measures. | Jiantao Jiao, Kartik Venkat, Yanjun Han, Tsachy Weissman |
| 2015 | ISIT | Minimax estimation of information measures. | Jiantao Jiao, Kartik Venkat, Yanjun Han, Tsachy Weissman |
| 2014 | ISIT | Information divergences and the curious case of the binary alphabet. | Jiantao Jiao, Thomas A. Courtade, Albert No, Kartik Venkat, Tsachy Weissman |
| 2014 | ISIT | Justification of logarithmic loss via the benefit of side information. | Jiantao Jiao, Thomas A. Courtade, Kartik Venkat, Tsachy Weissman |
| 2014 | ISIT | Relations between information and estimation in scalar Lvy channels. | Jiantao Jiao, Kartik Venkat, Tsachy Weissman |
| 2013 | ISIT | Pointwise relations between information and estimation in the Poisson channel. | Jiantao Jiao, Kartik Venkat, Tsachy Weissman |
| 2012 | ISIT | Universal estimation of directed information via sequential probability assignments. | Jiantao Jiao, Haim H. Permuter, Lei Zhao, Young-Han Kim, Tsachy Weissman |
| 2010 | SENSYS | NOMAD: networked-observation and mobile-agent-based scene abstraction and determination. | Lin Zhang, Wenzhu Zhang, Xinyu Mao, Jiantao Jiao, Shijie Zheng, Linglong Li, Yujie Liu, Teng Wang, Ming Gu |