Guan, Lin

11 publications

AAAI 2024 Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning Yantian Zha, Lin Guan, Subbarao Kambhampati

ICML 2024 Position: LLMs Can’t Plan, but Can Help Planning in LLM-Modulo Frameworks Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Mudit Verma, Kaya Stechly, Siddhant Bhambri, Lucas Paul Saldyt, Anil B Murthy

NeurIPS 2023 Leveraging Pre-Trained Large Language Models to Construct and Utilize World Models for Model-Based Task Planning Lin Guan, Karthik Valmeekam, Sarath Sreedharan, Subbarao Kambhampati

ICLR 2023 Relative Behavioral Attributes: Filling the Gap Between Symbolic Goal Specification and Reward Learning from Human Preferences Lin Guan, Karthik Valmeekam, Subbarao Kambhampati

ICMLW 2023 Relative Behavioral Attributes: Filling the Gap Between Symbolic Goal Specification and Reward Learning from Human Preferences Lin Guan, Karthik Valmeekam, Subbarao Kambhampati

ICML 2022 Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity Lin Guan, Sarath Sreedharan, Subbarao Kambhampati

AAAI 2022 Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems Subbarao Kambhampati, Sarath Sreedharan, Mudit Verma, Yantian Zha, Lin Guan

NeurIPS 2021 Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation Lin Guan, Mudit Verma, Suna Guo, Ruohan Zhang, Subbarao Kambhampati

AAAI 2020 Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset Ruohan Zhang, Calen Walshe, Zhuode Liu, Lin Guan, Karl S. Muller, Jake Alden Whritner, Luxin Zhang, Mary M. Hayhoe, Dana H. Ballard

NeurIPSW 2020 Explanation Augmented Feedback in Human-in-the-Loop Reinforcement Learning Lin Guan, Mudit Verma, Sihang Guo, Ruohan Zhang, Subbarao Kambhampati

IJCAI 2019 Leveraging Human Guidance for Deep Reinforcement Learning Tasks Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, Peter Stone