Multi-label HD Classification in 3D Flash. - Justin Morris; Yilun Hao; Saransh Gupta; Ranganathan Ramkumar; Jeffrey Yu; Mohsen Imani; Baris Aksanli; Tajana Rosing (VLSI-SOC, 2020)

Learning Feasibility to Imitate Demonstrators with Different Dynamics. - Zhangjie Cao; Yilun Hao; Mengxi Li; Dorsa Sadigh (CoRL, 2021)

Stochastic-HD: Leveraging Stochastic Computing on Hyper-Dimensional Computing. - Yilun Hao; Saransh Gupta; Justin Morris; Behnam Khaleghi; Baris Aksanli; Tajana Rosing (ICCD, 2021)

A Dual Representation Framework for Robot Learning with Human Guidance. - Ruohan Zhang; Dhruva Bansal; Yilun Hao; Ayano Hiranaka; Jialu Gao; Chen Wang 053; Roberto Martín-Martín; Li Fei-Fei 001; Jiajun Wu 001 (CoRL, 2022)

Weakly Supervised Correspondence Learning. - Zihan Wang; Zhangjie Cao; Yilun Hao; Dorsa Sadigh (ICRA, 2022)

Locality-Based Encoder and Model Quantization for Efficient Hyper-Dimensional Computing. - Justin Morris; Roshan Fernando; Yilun Hao; Mohsen Imani; Baris Aksanli; Tajana Rosing (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Gesture-Informed Robot Assistance via Foundation Models. - Li-Heng Lin; Yuchen Cui; Yilun Hao; Fei Xia 002; Dorsa Sadigh (CoRL, 2023)

NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities. - Ruohan Zhang; Sharon Lee; Minjune Hwang; Ayano Hiranaka; Chen Wang 053; Wensi Ai; Jin Jie Ryan Tan; Shreya Gupta; Yilun Hao; Gabrael Levine; Ruohan Gao; Anthony Norcia; et al. (CoRL, 2023)

Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations. - Yilun Hao; Ruinan Wang; Zhangjie Cao; Zihan Wang; Yuchen Cui; Dorsa Sadigh (IROS, 2023)

PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling. - Yongchao Chen; Jacob Arkin; Yilun Hao; Yang Zhang 001; Nicholas Roy; Chuchu Fan (EMNLP, 2024)

PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Preference Alignment. - Yongchao Chen; Jacob Arkin; Yilun Hao; Yang Zhang 001; Nicholas Roy; Chuchu Fan (CoRR, 2024)

Large Language Models Can Plan Your Travels Rigorously with Formal Verification Tools. - Yilun Hao; Yongchao Chen; Yang Zhang 001; Chuchu Fan (CoRR, 2024)

Predicting Organic-Inorganic Halide Perovskite Photovoltaic Performance from Optical Properties of Constituent Films through Machine Learning. - Ruiqi Zhang; Brandon Motes; Shaun Tan; Yongli Lu; Meng-Chen Shih; Yilun Hao; Karen Yang; Shreyas Srinivasan; Moungi G. Bawendi; Vladimir Bulovic (CoRR, 2024)

Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming. - Yilun Hao; Yang Zhang 001; Chuchu Fan (ICLR, 2025)

Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools. - Yilun Hao; Yongchao Chen; Yang Zhang 001; Chuchu Fan (NAACL (Long Papers), 2025)

CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance. - Yongchao Chen; Yilun Hao; Yueying Liu; Yang Zhang 001; Chuchu Fan (CoRR, 2025)

Code-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generation. - Yongchao Chen; Yilun Hao; Yang Zhang 001; Chuchu Fan (CoRR, 2025)

R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning. - Yongchao Chen; Yueying Liu; Junwei Zhou; Yilun Hao; Jingquan Wang; Yang Zhang 001; Chuchu Fan (CoRR, 2025)

Parallelism Meets Adaptiveness: Scalable Documents Understanding in Multi-Agent LLM Systems. - Chengxuan Xia; Qianye Wu; Sixuan Tian; Yilun Hao (CoRR, 2025)