Fangchen Liu

I am a fourth-year Ph.D. at UC Berkeley advised by Prof. Pieter Abbeel. Prior to that, I obtained my M.S. from UC San Diego working with Prof. Hao Su, and B.S. from Peking University. I'm generally interested in machine learning and robotics.

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fangchen_liu [at] berkeley [dot] edu

Publications

MOKA: Open-Vocabulary Robotic Manipulation through Mark-based Visual Prompting Fangchen Liu*, Kuan Fang*, Pieter Abbeel, Sergey Levine RSS 2024 Paper / Code

Chain-of-Thought Predictive Control Zhiwei Jia, Fangchen Liu, Vineet Thumuiluri, Linghao Chen, Zhiao Huang, Hao Su ICML 2024 Paper / Code

FMB: a Functional Manipulation Benchmark for Generalizable Robotic Learning Jianlan Luo*, Charles Xu*, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine IJRR 2024 Paper / Code

SpawnNet: Learning Generalizable Visuomotor Skills from Pre-trained Networks Xingyu Lin, John So, Sashwat Mahalingam, Fangchen Liu, Pieter Abbeel ICRA 2024 Paper / Code

The Wisdom of Hindsight Makes Language Models Better Instruction Followers Tianjun Zhang*, Fangchen Liu*, Justin Wong, Pieter Abbeel, Joseph E. Gonzalez. ICML 2023 Paper / Code

Masked Autoencoding for Scalable and Generalizable Decision Making Fangchen Liu*, Hao Liu*, Aditya Grover, Pieter Abbeel. NeurIPS 2022 Paper / Code

Towards More Generalizable One-shot Visual Imitation Learning Zhao Mandi*, Fangchen Liu*, Kimin Lee, Pieter Abbeel. ICRA 2022 Paper / Code

Masked World Models for Visual Control Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel. CoRL 2022 Paper / Code

State Alignment-based Imitation Learning Fangchen Liu, Zhan Ling, Tongzhou Mu, Hao Su ICLR 2020 Paper / Code

Mapping State Space using Landmarks for Universal Goal Reaching Zhiao Huang*, Fangchen Liu*, Hao Su NeurIPS 2019 Paper / Code

SAPIEN: a SimulAted Part-based Interactive ENvironment Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, Li Yi, He Wang, Angel Chang, Leonidas Guibas, Hao Su. CVPR 2020 (oral) Paper / Project Page

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning. Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vash Madhavan, Trevor Darrell CVPR 2020 (oral) Paper / Code

Education

University of California, Berkeley

Aug. 2020 - Present

Ph.D. in Computer Science

University of California, San Diego

Sep. 2018 - Mar. 2020

M.S. in Computer Science

Peking University

Sep. 2014 - Jul. 2018

B.S. in Computer Science (Summa Cum Laude)

Experience