PAC Continuous State Online Multitask Reinforcement Learning with Identification. - Yao Liu 009; Zhaohan Guo; Emma Brunskill (AAMAS, 2016)

Representation Balancing MDPs for Off-policy Policy Evaluation. - Yao Liu 009; Omer Gottesman; Aniruddh Raghu; Matthieu Komorowski; Aldo A. Faisal; Finale Doshi-Velez; Emma Brunskill (NeurIPS, 2018)

When Simple Exploration is Sample Efficient: Identifying Sufficient Conditions for Random Exploration to Yield PAC RL Algorithms. - Yao Liu 009; Emma Brunskill (CoRR, 2018)

Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. - Aniruddh Raghu; Omer Gottesman; Yao Liu 009; Matthieu Komorowski; Aldo Faisal; Finale Doshi-Velez; Emma Brunskill (CoRR, 2018)

Combining parametric and nonparametric models for off-policy evaluation. - Omer Gottesman; Yao Liu 009; Scott Sussex; Emma Brunskill; Finale Doshi-Velez (ICML, 2019)

Off-Policy Policy Gradient with Stationary Distribution Correction. - Yao Liu 009; Adith Swaminathan; Alekh Agarwal; Emma Brunskill (UAI, 2019)

Off-Policy Policy Gradient with State Distribution Correction. - Yao Liu 009; Adith Swaminathan; Alekh Agarwal; Emma Brunskill (CoRR, 2019)

All-Action Policy Gradient Methods: A Numerical Integration Approach. - Benjamin Petit; Loren Amdahl-Culleton; Yao Liu 009; Jimmy Smith; Pierre-Luc Bacon (CoRR, 2019)

Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling. - Yao Liu 009; Pierre-Luc Bacon; Emma Brunskill (ICML, 2020)

Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. - Omer Gottesman; Joseph Futoma; Yao Liu 009; Sonali Parbhoo; Leo A. Celi; Emma Brunskill; Finale Doshi-Velez (ICML, 2020)

Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration. - Yao Liu 009; Adith Swaminathan; Alekh Agarwal; Emma Brunskill (NeurIPS, 2020)

Provably Good Batch Reinforcement Learning Without Great Exploration. - Yao Liu 009; Adith Swaminathan; Alekh Agarwal; Emma Brunskill (CoRR, 2020)

Adaptive and efficient batch reinforcement learning algorithms. - Yao Liu 009 (2021)

Offline policy optimization with eligible actions. - Yao Liu 009; Yannis Flet-Berliac; Emma Brunskill (UAI, 2022)

Budgeting Counterfactual for Offline RL. - Yao Liu 009; Pratik Chaudhari; Rasool Fakoor (NeurIPS, 2023)

TD Convergence: An Optimization Perspective. - Kavosh Asadi; Shoham Sabach; Yao Liu 009; Omer Gottesman; Rasool Fakoor (NeurIPS, 2023)

Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task. - Sherry Ruan; Allen Nie; William Steenbergen; Jiayu He; JQ Zhang; Meng Guo 006; Yao Liu 009; Kyle Dang Nguyen; Catherine Y. Wang; Rui Ying; James A. Landay; Emma Brunskill (CoRR, 2023)

EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data. - Jesse Zhang; Minho Heo; Zuxin Liu; Erdem Biyik; Joseph J. Lim; Yao Liu 009; Rasool Fakoor (CoRL, 2024)

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. - Zuxin Liu; Jesse Zhang; Kavosh Asadi; Yao Liu 009; Ding Zhao; Shoham Sabach; Rasool Fakoor (ICLR, 2024)

Learning the Target Network in Function Space. - Kavosh Asadi; Yao Liu 009; Shoham Sabach; Ming Yin; Rasool Fakoor (ICML, 2024)

EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. - Jesse Zhang; Minho Heo; Zuxin Liu; Erdem Biyik; Joseph J. Lim; Yao Liu 009; Rasool Fakoor (CoRR, 2024)

Reinforcement learning tutor better supported lower performers in a math task. - Sherry Ruan; Allen Nie; William Steenbergen; Jiayu He; J. Q. Zhang; Meng Guo 006; Yao Liu 009; Kyle Dang Nguyen; Catherine Y. Wang; Rui Ying; James A. Landay; Emma Brunskill (Mach. Learn., 2024)

AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. - Ke Yang 003; Yao Liu 009; Sapana Chaudhary; Rasool Fakoor; Pratik Chaudhari; George Karypis; Huzefa Rangwala (ICLR, 2025)

Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. - Zhepeng Cen; Yao Liu 009; Siliang Zeng; Pratik Chaudhari; Huzefa Rangwala; George Karypis; Rasool Fakoor (Trans. Mach. Learn. Res., 2025)

From Demonstrations to Rewards: Alignment Without Explicit Human Preferences. - Siliang Zeng; Yao Liu 009; Huzefa Rangwala; George Karypis; Mingyi Hong 001; Rasool Fakoor (CoRR, 2025)

Teaching Large Language Models to Reason through Learning and Forgetting. - Tianwei Ni; Allen Nie; Sapana Chaudhary; Yao Liu 009; Huzefa Rangwala; Rasool Fakoor (CoRR, 2025)