Yao Liu - RankMe

38 papers A* 10A 3Misc 1Journal 23

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. ICLR Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala
2025	J	`jnl`	Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. Trans. Mach. Learn. Res. Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor
2025	J	`jnl`	From Demonstrations to Rewards: Alignment Without Explicit Human Preferences. CoRR Siliang Zeng, Yao Liu, Huzefa Rangwala, George Karypis, Mingyi Hong, Rasool Fakoor
2025	J	`jnl`	Offline Learning and Forgetting for Reasoning with Large Language Models. Trans. Mach. Learn. Res. Tianwei Ni, Allen Nie, Sapana Chaudhary, Yao Liu, Huzefa Rangwala, Rasool Fakoor
2025	J	`jnl`	Teaching Large Language Models to Reason through Learning and Forgetting. CoRR Tianwei Ni, Allen Nie, Sapana Chaudhary, Yao Liu, Huzefa Rangwala, Rasool Fakoor
2024	J	`jnl`	AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. CoRR Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala
2024	J	`jnl`	Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. CoRR Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor
2024	Misc	`conf`	EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data. CoRL Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor
2024	J	`jnl`	EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. CoRR Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor
2024	A*	`conf`	Learning the Target Network in Function Space. ICML Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor
2024	J	`jnl`	Learning the Target Network in Function Space. CoRR Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor
2024	J	`jnl`	Reinforcement learning tutor better supported lower performers in a math task. Mach. Learn. Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, J. Q. Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill
2024	A*	`conf`	TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. ICLR Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
2023	A*	`conf`	Budgeting Counterfactual for Offline RL. NeurIPS Yao Liu, Pratik Chaudhari, Rasool Fakoor
2023	J	`jnl`	Budgeting Counterfactual for Offline RL. CoRR Yao Liu, Pratik Chaudhari, Rasool Fakoor
2023	J	`jnl`	Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task. CoRR Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, JQ Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill
2023	J	`jnl`	TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. CoRR Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
2023	A*	`conf`	TD Convergence: An Optimization Perspective. NeurIPS Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
2023	J	`jnl`	TD Convergence: An Optimization Perspective. CoRR Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
2022	J	`jnl`	Offline Policy Optimization with Eligible Actions. CoRR Yao Liu, Yannis Flet-Berliac, Emma Brunskill
2022	A	`conf`	Offline policy optimization with eligible actions. UAI Yao Liu, Yannis Flet-Berliac, Emma Brunskill
2021	—	`—`	Adaptive and efficient batch reinforcement learning algorithms. Yao Liu
2020	A*	`conf`	Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. ICML Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez
2020	J	`jnl`	Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. CoRR Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez
2020	A*	`conf`	Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration. NeurIPS Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2020	J	`jnl`	Provably Good Batch Reinforcement Learning Without Great Exploration. CoRR Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2020	A*	`conf`	Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling. ICML Yao Liu, Pierre-Luc Bacon, Emma Brunskill
2019	J	`jnl`	All-Action Policy Gradient Methods: A Numerical Integration Approach. CoRR Benjamin Petit, Loren Amdahl-Culleton, Yao Liu, Jimmy Smith, Pierre-Luc Bacon
2019	J	`jnl`	Combining Parametric and Nonparametric Models for Off-Policy Evaluation. CoRR Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
2019	A*	`conf`	Combining parametric and nonparametric models for off-policy evaluation. ICML Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
2019	J	`jnl`	Off-Policy Policy Gradient with State Distribution Correction. CoRR Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2019	A	`conf`	Off-Policy Policy Gradient with Stationary Distribution Correction. UAI Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2019	J	`jnl`	Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling. CoRR Yao Liu, Pierre-Luc Bacon, Emma Brunskill
2018	J	`jnl`	Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. CoRR Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
2018	J	`jnl`	Representation Balancing MDPs for Off-Policy Policy Evaluation. CoRR Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
2018	A*	`conf`	Representation Balancing MDPs for Off-policy Policy Evaluation. NeurIPS Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A. Faisal, Finale Doshi-Velez, Emma Brunskill
2018	J	`jnl`	When Simple Exploration is Sample Efficient: Identifying Sufficient Conditions for Random Exploration to Yield PAC RL Algorithms. CoRR Yao Liu, Emma Brunskill
2016	A	`conf`	PAC Continuous State Online Multitask Reinforcement Learning with Identification. AAMAS Yao Liu, Zhaohan Guo, Emma Brunskill