Tengyang Xie

According to our database, Tengyang Xie authored at least 35 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Understanding Behavior Cloning with Action Quantization.

Haoqun Cao, Tengyang Xie

CoRR, March, 2026

Breaking the Capability Ceiling of LLM Post-Training by Reintroducing Markov States.

Yurun Yuan, Tengyang Xie

CoRR, March, 2026

POLCA: Stochastic Generative Optimization with LLM.

Xuanfei Ren, Allen Nie, Tengyang Xie, Ching-An Cheng

CoRR, March, 2026

2025

Offline Reinforcement Learning in Large State Spaces: Algorithms and Guarantees.

Nan Jiang, Tengyang Xie

CoRR, October, 2025

Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning.

Yurun Yuan, Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits.

Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Reinforce LLM Reasoning through Multi-Agent Reflection.

Yurun Yuan, Tengyang Xie

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective.

Zeyu Jia, Alexander Rakhlin, Tengyang Xie

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF.

Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Hassan Awadallah, Alexander Rakhlin

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization.

Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Self-Play with Adversarial Critic: Provable and Scalable Offline Alignment for Language Models.

Xiang Ji, Sanjeev Kulkarni, Mengdi Wang, Tengyang Xie

CoRR, 2024

Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences.

Corby Rosset, Ching-An Cheng, Arindam Mitra, Michael Santacroce, Ahmed Awadallah, Tengyang Xie

CoRR, 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data.

Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Principled Representation Learning from Videos for Reinforcement Learning.

Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Harnessing Density Ratios for Online Reinforcement Learning.

Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts.

Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

CounterCurate: Enhancing Physical and Semantic Visio-Linguistic Compositional Reasoning via Counterfactual Examples.

Jianrui Zhang, Mu Cai, Tengyang Xie, Yong Jae Lee

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Adversarial Model for Offline Reinforcement Learning.

Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Role of Coverage in Online Reinforcement Learning.

Tengyang Xie, Dylan J. Foster, Yu Bai, Nan Jiang, Sham M. Kakade

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

ARMOR: A Model-based Framework for Improving Arbitrary Baseline Policies with Offline Data.

Tengyang Xie, Mohak Bhardwaj, Nan Jiang, Ching-An Cheng

CoRR, 2022

Interaction-Grounded Learning with Action-Inclusive Feedback.

Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adversarially Trained Actor Critic for Offline Reinforcement Learning.

Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal

Proceedings of the International Conference on Machine Learning, 2022

2021

Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency.

Masatoshi Uehara, Masaaki Imaizumi, Nan Jiang, Nathan Kallus, Wen Sun, Tengyang Xie

CoRR, 2021

Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning.

Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bellman-consistent Pessimism for Offline Reinforcement Learning.

Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Batch Value-function Approximation with Only Realizability.

Tengyang Xie, Nan Jiang

Proceedings of the 38th International Conference on Machine Learning, 2021

Interaction-Grounded Learning.

Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting.

Philip Amortila, Nan Jiang, Tengyang Xie

CoRR, 2020

Q^* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison.

Tengyang Xie, Nan Jiang

CoRR, 2020

Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison.

Tengyang Xie, Nan Jiang

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling.

Tengyang Xie, Yifei Ma, Yu-Xiang Wang

CoRR, 2019

Privacy Preserving Off-Policy Evaluation.

Tengyang Xie, Philip S. Thomas, Gerome Miklau

CoRR, 2019

Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling.

Tengyang Xie, Yifei Ma, Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Provably Efficient Q-Learning with Low Switching Cost.

Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A Block Coordinate Ascent Algorithm for Mean-Variance Optimization.

Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018