Tengyu Xu - RankMe

47 papers A* 12A 3Journal 30Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Boosting LLM Reasoning via Spontaneous Self-Correction. CoRR Xutong Zhao, Tengyu Xu, Xuewei Wang, Zhengxing Chen, Di Jin, Liang Tan, Yen-Ting, Zishun Yu, Zhuokai Zhao, Yun He, Sinong Wang, Han Fang, Sarath Chandar, Chenguang Zhu
2025	—	`conf`	HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback. KDD (1) Xufeng Cai, Ziwei Guan, Lei Yuan, Ali Selman Aydin, Tengyu Xu, Boying Liu, Wenbo Ren, Renkai Xiang, Songyi He, Haichuan Yang, Serena Li, Mingze Gao, Yue Weng, Ji Liu
2025	J	`jnl`	HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback. CoRR Xufeng Cai, Ziwei Guan, Lei Yuan, Ali Selman Aydin, Tengyu Xu, Boying Liu, Wenbo Ren, Renkai Xiang, Songyi He, Haichuan Yang, Serena Li, Mingze Gao, Yue Weng, Ji Liu
2025	—	`conf`	Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation. ACL (2) Chengwei Qin, Wenxuan Zhou, Karthik Abinav Sankararaman, Nanshu Wang, Tengyu Xu, Alexander Radovic, Eryk Helenowski, Arya Talebzadeh, Aditya Tayade, Sinong Wang, Shafiq Joty, Han Fang, Hao Ma
2025	J	`jnl`	Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation. CoRR Chengwei Qin, Wenxuan Zhou, Karthik Abinav Sankararaman, Nanshu Wang, Tengyu Xu, Alexander Radovic, Eryk Helenowski, Arya Talebzadeh, Aditya Tayade, Sinong Wang, Shafiq Joty, Han Fang, Hao Ma
2025	J	`jnl`	LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training. CoRR Bo Wu, Sid Wang, Yunhao Tang, Jia Ding, Eryk Helenowski, Liang Tan, Tengyu Xu, Tushar Gowda, Zhengxing Chen, Chen Zhu, Xiaocheng Tang, Yundi Qian, Beibei Zhu, Rui Hou
2025	J	`jnl`	Reinforcement Learning from User Feedback. CoRR Eric Han, Jun Chen, Karthik Abinav Sankararaman, Xiaoliang Peng, Tengyu Xu, Eryk Helenowski, Kaiyan Peng, Mrinal Kumar, Sinong Wang, Han Fang, Arya Talebzadeh
2025	J	`jnl`	Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback. CoRR Yen-Ting Lin, Di Jin, Tengyu Xu, Tianhao Wu, Sainbayar Sukhbaatar, Chen Zhu, Yun He, Yun-Nung Chen, Jason Weston, Yuandong Tian, Arash Rahnama, Sinong Wang, Hao Ma, Han Fang
2025	A*	`conf`	Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization. ICML Zishun Yu, Tengyu Xu, Di Jin, Karthik Abinav Sankararaman, Yun He, Wenxuan Zhou, Zhouhao Zeng, Eryk Helenowski, Chen Zhu, Sinong Wang, Hao Ma, Han Fang
2025	J	`jnl`	Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization. CoRR Zishun Yu, Tengyu Xu, Di Jin, Karthik Abinav Sankararaman, Yun He, Wenxuan Zhou, Zhouhao Zeng, Eryk Helenowski, Chen Zhu, Sinong Wang, Hao Ma, Han Fang
2024	J	`jnl`	Faster algorithm and sharper analysis for constrained Markov decision process. Oper. Res. Lett. Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
2024	J	`jnl`	Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following. CoRR Yun He, Di Jin, Chaoqi Wang, Chloe Bi, Karishma Mandyam, Hejia Zhang, Chen Zhu, Ning Li, Tengyu Xu, Hongjiang Lv, Shruti Bhosale, Chenguang Zhu, Karthik Abinav Sankararaman, Eryk Helenowski, Melanie Kambadur, Aditya Tayade, Hao Ma, Han Fang, Sinong Wang
2024	J	`jnl`	Provably Efficient Offline Reinforcement Learning With Trajectory-Wise Reward. IEEE Trans. Inf. Theory Tengyu Xu, Yue Wang, Shaofeng Zou, Yingbin Liang
2024	J	`jnl`	The Perfect Blend: Redefining RLHF with Mixture of Judges. CoRR Tengyu Xu, Eryk Helenowski, Karthik Abinav Sankararaman, Di Jin, Kaiyan Peng, Eric Han, Shaoliang Nie, Chen Zhu, Hejia Zhang, Wenxuan Zhou, Zhouhao Zeng, Yun He, Karishma Mandyam, Arya Talabzadeh, Madian Khabsa, Gabriel Cohen, Yuandong Tian, Hao Ma, Sinong Wang, Han Fang
2023	J	`jnl`	Constraint-based multi-agent reinforcement learning for collaborative tasks. Comput. Animat. Virtual Worlds Xiumin Shang, Tengyu Xu, Ioannis Karamouzas, Marcelo Kallmann
2022	A*	`conf`	A Unifying Framework of Off-Policy General Value Function Evaluation. NeurIPS Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2022	A	`conf`	Deterministic policy gradient: Convergence analysis. UAI Huaqing Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang
2022	A*	`conf`	Model-Based Offline Meta-Reinforcement Learning with Regularization. ICLR Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang
2022	J	`jnl`	Model-Based Offline Meta-Reinforcement Learning with Regularization. CoRR Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang
2022	A*	`conf`	PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method. ICLR Ziwei Guan, Tengyu Xu, Yingbin Liang
2022	J	`jnl`	Provably Efficient Offline Reinforcement Learning with Trajectory-Wise Reward. CoRR Tengyu Xu, Yingbin Liang
2021	J	`jnl`	A Unified Off-Policy Evaluation Approach for General Value Function. CoRR Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2021	A*	`conf`	CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee. ICML Tengyu Xu, Yingbin Liang, Guanghui Lan
2021	A*	`conf`	Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. ICML Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2021	J	`jnl`	Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. CoRR Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2021	J	`jnl`	Faster Algorithm and Sharper Analysis for Constrained Markov Decision Process. CoRR Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
2021	A*	`conf`	Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling. AAAI Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang
2021	J	`jnl`	PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method. CoRR Ziwei Guan, Tengyu Xu, Yingbin Liang
2021	A*	`conf`	Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry. ICLR Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
2021	J	`jnl`	Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry. CoRR Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
2021	A	`conf`	Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms. AISTATS Tengyu Xu, Yingbin Liang
2021	A	`conf`	When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence. AISTATS Ziwei Guan, Tengyu Xu, Yingbin Liang
2020	J	`jnl`	A Primal Approach to Constrained Policy Optimization: Global Optimality and Finite-Time Analysis. CoRR Tengyu Xu, Yingbin Liang, Guanghui Lan
2020	J	`jnl`	Enhanced First and Zeroth Order Variance Reduced Algorithms for Min-Max Optimization. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang, H. Vincent Poor
2020	A*	`conf`	Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms. NeurIPS Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Improving Sample Complexity Bounds for Actor-Critic Algorithms. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling. CoRR Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang
2020	A*	`conf`	Reanalysis of Variance Reduced Temporal Difference Learning. ICLR Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang
2020	J	`jnl`	Reanalysis of Variance Reduced Temporal Difference Learning. CoRR Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang
2020	J	`jnl`	Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms. CoRR Tengyu Xu, Yingbin Liang
2020	J	`jnl`	When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence. CoRR Ziwei Guan, Tengyu Xu, Yingbin Liang
2019	J	`jnl`	Finite-Sample Analysis for SARSA and Q-Learning with Linear Function Approximation. CoRR Shaofeng Zou, Tengyu Xu, Yingbin Liang
2019	A*	`conf`	Finite-Sample Analysis for SARSA with Linear Function Approximation. NeurIPS Shaofeng Zou, Tengyu Xu, Yingbin Liang
2019	A*	`conf`	Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples. NeurIPS Tengyu Xu, Shaofeng Zou, Yingbin Liang
2019	J	`jnl`	Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples. CoRR Tengyu Xu, Shaofeng Zou, Yingbin Liang
2018	J	`jnl`	Convergence of SGD in Learning ReLU Models with Separable Data. CoRR Tengyu Xu, Yi Zhou, Kaiyi Ji, Yingbin Liang