Tengyang Xie - RankMe

54 papers A* 18A 1Journal 33Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Breaking the Capability Ceiling of LLM Post-Training by Reintroducing Markov States. CoRR Yurun Yuan, Tengyang Xie
2026	J	`jnl`	POLCA: Stochastic Generative Optimization with LLM. CoRR Xuanfei Ren, Allen Nie, Tengyang Xie, Ching-An Cheng
2026	J	`jnl`	Understanding Behavior Cloning with Action Quantization. CoRR Haoqun Cao, Tengyang Xie
2025	A*	`conf`	Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. ICLR Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
2025	A*	`conf`	Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective. ICML Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2025	J	`jnl`	Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective. CoRR Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2025	A*	`conf`	Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF. ICLR Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Hassan Awadallah, Alexander Rakhlin
2025	J	`jnl`	Offline Reinforcement Learning in Large State Spaces: Algorithms and Guarantees. CoRR Nan Jiang, Tengyang Xie
2025	J	`jnl`	Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits. CoRR Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2025	A*	`conf`	Reinforce LLM Reasoning through Multi-Agent Reflection. ICML Yurun Yuan, Tengyang Xie
2025	J	`jnl`	Reinforce LLM Reasoning through Multi-Agent Reflection. CoRR Yurun Yuan, Tengyang Xie
2025	J	`jnl`	Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning. CoRR Yurun Yuan, Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2024	J	`jnl`	Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. CoRR Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
2024	—	`conf`	CounterCurate: Enhancing Physical and Semantic Visio-Linguistic Compositional Reasoning via Counterfactual Examples. ACL (Findings) Jianrui Zhang, Mu Cai, Tengyang Xie, Yong Jae Lee
2024	J	`jnl`	CounterCurate: Enhancing Physical and Semantic Visio-Linguistic Compositional Reasoning via Counterfactual Examples. CoRR Jianrui Zhang, Mu Cai, Tengyang Xie, Yong Jae Lee
2024	J	`jnl`	Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences. CoRR Corby Rosset, Ching-An Cheng, Arindam Mitra, Michael Santacroce, Ahmed Awadallah, Tengyang Xie
2024	J	`jnl`	Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF. CoRR Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Awadallah, Alexander Rakhlin
2024	A*	`conf`	Harnessing Density Ratios for Online Reinforcement Learning. ICLR Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
2024	J	`jnl`	Harnessing Density Ratios for Online Reinforcement Learning. CoRR Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
2024	—	`conf`	Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. EMNLP (Findings) Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024	J	`jnl`	Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. CoRR Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024	A*	`conf`	Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. ICML Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar
2024	J	`jnl`	Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. CoRR Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar
2024	J	`jnl`	Self-Play with Adversarial Critic: Provable and Scalable Offline Alignment for Language Models. CoRR Xiang Ji, Sanjeev Kulkarni, Mengdi Wang, Tengyang Xie
2024	A*	`conf`	Towards Principled Representation Learning from Videos for Reinforcement Learning. ICLR Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
2024	J	`jnl`	Towards Principled Representation Learning from Videos for Reinforcement Learning. CoRR Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
2023	A*	`conf`	Adversarial Model for Offline Reinforcement Learning. NeurIPS Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
2023	J	`jnl`	Adversarial Model for Offline Reinforcement Learning. CoRR Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
2023	A*	`conf`	The Role of Coverage in Online Reinforcement Learning. ICLR Tengyang Xie, Dylan J. Foster, Yu Bai, Nan Jiang, Sham M. Kakade
2022	J	`jnl`	ARMOR: A Model-based Framework for Improving Arbitrary Baseline Policies with Offline Data. CoRR Tengyang Xie, Mohak Bhardwaj, Nan Jiang, Ching-An Cheng
2022	A*	`conf`	Adversarially Trained Actor Critic for Offline Reinforcement Learning. ICML Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
2022	J	`jnl`	Adversarially Trained Actor Critic for Offline Reinforcement Learning. CoRR Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
2022	A*	`conf`	Interaction-Grounded Learning with Action-Inclusive Feedback. NeurIPS Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
2022	J	`jnl`	Interaction-Grounded Learning with Action-inclusive Feedback. CoRR Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
2022	J	`jnl`	The Role of Coverage in Online Reinforcement Learning. CoRR Tengyang Xie, Dylan J. Foster, Yu Bai, Nan Jiang, Sham M. Kakade
2021	A*	`conf`	Batch Value-function Approximation with Only Realizability. ICML Tengyang Xie, Nan Jiang
2021	A*	`conf`	Bellman-consistent Pessimism for Offline Reinforcement Learning. NeurIPS Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
2021	J	`jnl`	Bellman-consistent Pessimism for Offline Reinforcement Learning. CoRR Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
2021	J	`jnl`	Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency. CoRR Masatoshi Uehara, Masaaki Imaizumi, Nan Jiang, Nathan Kallus, Wen Sun, Tengyang Xie
2021	A*	`conf`	Interaction-Grounded Learning. ICML Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021	J	`jnl`	Interaction-Grounded Learning. CoRR Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021	A*	`conf`	Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning. NeurIPS Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
2021	J	`jnl`	Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning. CoRR Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
2020	J	`jnl`	A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting. CoRR Philip Amortila, Nan Jiang, Tengyang Xie
2020	J	`jnl`	Batch Value-function Approximation with Only Realizability. CoRR Tengyang Xie, Nan Jiang
2020	J	`jnl`	Q CoRR Tengyang Xie, Nan Jiang
2020	A	`conf`	Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison. UAI Tengyang Xie, Nan Jiang
2019	J	`jnl`	Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling. CoRR Tengyang Xie, Yifei Ma, Yu-Xiang Wang
2019	J	`jnl`	Privacy Preserving Off-Policy Evaluation. CoRR Tengyang Xie, Philip S. Thomas, Gerome Miklau
2019	A*	`conf`	Provably Efficient Q-Learning with Low Switching Cost. NeurIPS Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang
2019	J	`jnl`	Provably Efficient Q-Learning with Low Switching Cost. CoRR Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang
2019	A*	`conf`	Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling. NeurIPS Tengyang Xie, Yifei Ma, Yu-Xiang Wang
2018	A*	`conf`	A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. NeurIPS Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
2018	J	`jnl`	A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. CoRR Bo Liu, Tengyang Xie, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon