Tengyang Xie

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 40

Top Topics

Function Approximation

Reinforcement Learning

Importance Sampling

Top Venues

Publications

Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. CoRR (2024)
Jianrui Zhang, Mu Cai, Tengyang Xie, Yong Jae Lee
CounterCurate: Enhancing Physical and Semantic Visio-Linguistic Compositional Reasoning via Counterfactual Examples. CoRR (2024)
Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Awadallah, Alexander Rakhlin
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF. CoRR (2024)
Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
Towards Principled Representation Learning from Videos for Reinforcement Learning. ICLR (2024)
Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. CoRR (2024)
Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
Harnessing Density Ratios for Online Reinforcement Learning. CoRR (2024)
Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. CoRR (2024)
Xiang Ji, Sanjeev Kulkarni, Mengdi Wang, Tengyang Xie
Self-Play with Adversarial Critic: Provable and Scalable Offline Alignment for Language Models. CoRR (2024)
Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
Towards Principled Representation Learning from Videos for Reinforcement Learning. CoRR (2024)
Jianrui Zhang, Mu Cai, Tengyang Xie, Yong Jae Lee
CounterCurate: Enhancing Physical and Semantic Visio-Linguistic Compositional Reasoning via Counterfactual Examples. ACL (Findings) (2024)
Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
Harnessing Density Ratios for Online Reinforcement Learning. ICLR (2024)
Corby Rosset, Ching-An Cheng, Arindam Mitra, Michael Santacroce, Ahmed Awadallah, Tengyang Xie
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences. CoRR (2024)
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
Adversarial Model for Offline Reinforcement Learning. CoRR (2023)
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
Adversarial Model for Offline Reinforcement Learning. NeurIPS (2023)
Tengyang Xie, Dylan J. Foster, Yu Bai, Nan Jiang, Sham M. Kakade
The Role of Coverage in Online Reinforcement Learning. ICLR (2023)
Tengyang Xie, Dylan J. Foster, Yu Bai, Nan Jiang, Sham M. Kakade
The Role of Coverage in Online Reinforcement Learning. CoRR (2022)
Tengyang Xie, Mohak Bhardwaj, Nan Jiang, Ching-An Cheng
ARMOR: A Model-based Framework for Improving Arbitrary Baseline Policies with Offline Data. CoRR (2022)
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
Adversarially Trained Actor Critic for Offline Reinforcement Learning. ICML (2022)
Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
Interaction-Grounded Learning with Action-Inclusive Feedback. NeurIPS (2022)
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
Adversarially Trained Actor Critic for Offline Reinforcement Learning. CoRR (2022)
Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
Interaction-Grounded Learning with Action-inclusive Feedback. CoRR (2022)
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
Interaction-Grounded Learning. CoRR (2021)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Bellman-consistent Pessimism for Offline Reinforcement Learning. CoRR (2021)
Tengyang Xie, Nan Jiang
Batch Value-function Approximation with Only Realizability. ICML (2021)
Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning. CoRR (2021)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Bellman-consistent Pessimism for Offline Reinforcement Learning. NeurIPS (2021)
Masatoshi Uehara, Masaaki Imaizumi, Nan Jiang, Nathan Kallus, Wen Sun, Tengyang Xie
Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency. CoRR (2021)
Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning. NeurIPS (2021)
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
Interaction-Grounded Learning. ICML (2021)
Tengyang Xie, Nan Jiang
Batch Value-function Approximation with Only Realizability. CoRR (2020)
Tengyang Xie, Nan Jiang
Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison. UAI (2020)
Philip Amortila, Nan Jiang, Tengyang Xie
A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting. CoRR (2020)
Tengyang Xie, Nan Jiang
Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison. CoRR (2020)
Tengyang Xie, Philip S. Thomas, Gerome Miklau
Privacy Preserving Off-Policy Evaluation. CoRR (2019)
Tengyang Xie, Yifei Ma, Yu-Xiang Wang
Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling. CoRR (2019)
Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang
Provably Efficient Q-Learning with Low Switching Cost. NeurIPS (2019)
Tengyang Xie, Yifei Ma, Yu-Xiang Wang
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling. NeurIPS (2019)
Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang
Provably Efficient Q-Learning with Low Switching Cost. CoRR (2019)
Bo Liu, Tengyang Xie, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. CoRR (2018)
Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. NeurIPS (2018)