Zhan Ling

PhD student, UC San Diego

z6ling [at] ucsd [dot] edu

I am a Ph.D. candidate at UC San Diego, advised by Prof. Hao Su. Before starting my Ph.D., I graduated from Yao Class at Tsinghua University.

Research interest

My research interests focus on developing an intelligent agent capable of solving a wide range of tasks and learning from interactions with the environment. I have extensively explored several areas, including imitation learning, reinforcement learning, physical simulation, robotics, and reasoning. Currently, my primary research objective is to enhance the reasoning capabilities of foundation models.

Publications and preprints

Papers sorted by recency(*/**/*** = equal contribution). Representative papers are highlighted.

Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving
Zhan Ling, Yunhao Fang, Xuanlin Li, Tongzhou Mu, Mingu Lee, Reza Pourreza, Roland Memisevic, Hao Su
Preprint
arXiv / code
Deductive Verification of Chain-of-Thought Reasoning
Zhan Ling*, Yunhao Fang*, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, Hao Su
Neural Information Processing Systems (NeurIPS), 2023
arXiv / code / poster
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability
Xuanlin Li*, Yunhao Fang*, Minghua Liu, Zhan Ling, Zhuowen Tu, Hao Su
IEEE / CVF International Conference on Computer Vision (ICCV), 2023
arXiv / code poster
On the Efficacy of 3D Point Cloud Reinforcement Learning
Zhan Ling*, Yunchao Yao*, Xuanling Li, Hao Su
Preprint
arXiv / code
Reparameterized Policy Learning for Multimodal Trajectory Optimization
Zhiao Huang, Litian Liang, Zhan Ling, Xuanlin Li, Chuang Gan, Hao Su
International Conference on Machine Learning (ICML), 2023, (Oral)
arXiv / code / website / video
PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models
Minghua Liu, Yinhao Zhu, Hong Cai, Shizhong Han, Zhan Ling, Fatih Porikli, Hao Su
IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023
arXiv / code(coming soon) / website / video / slides
ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
Jiayuan Gu*, Fanbo Xiang*, Xuanlin Li**, Zhan Ling**, Xiqiang Liu**, Tongzhou Mu**, Yihe Tang**, Stone Tao**, Xinyue Wei**, Yunchao Yao**, Xiaodi Yuan, Pengwei Xie, Zhiao Huang, Rui Chen, Hao Su
International Conference on Learning Representations (ICLR), 2023
arXiv / code / website / video / challenge website / baseline code
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds
Minghua Liu*, Xuanlin Li*, Zhan Ling*, Yangyan Li, Hao Su
Conference on Robot Learning (CoRL), 2022
arXiv / code / website / video / slides
Improving policy optimization with generalist-specialist learning
Zhiwei Jia, Xuanlin Li, Zhan Ling, Shuang Liu, Yiran Wu, Hao Su
International Conference on Machine Learning (ICML), 2022
arXiv / code / website
Close the Visual Domain Gap by Physics-Grounded Active Stereovision Depth Sensor Simulation
Xiaoshuai Zhang*, Rui Chen*, Ang Li**, Fanbo Xiang**, Yuzhe Qin**, Jiayuan Gu**, Zhan Ling**, Minghua Liu**, Peiyu Zeng**, Songfang Han***, Zhiao Huang***, Tongzhou Mu***, Jing Xu, Hao Su
IEEE Transactions on Robotics (T-RO) & IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
arXiv / code
ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
Tongzhou Mu*, Zhan Ling*, Fanbo Xiang*, Derek Yang*, Xuanlin Li*, Stone Tao, Zhiao Huang, Zhiwei Jia, Hao Su
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2021
arXiv / code / website / video / slides / baseline code / poster
State Alignment-based Imitation Learning
Fangchen Liu, Zhan Ling, Tongzhou Mu, Hao Su
International Conference on Learning Representations (ICLR), 2020
arXiv / code

Services

Conference Reviewer: ICLR, ICML, NeurIPS, CVPR, ICCV, ECCV, ACCV.
Journal Reviewer: T-RO, RA-L.

Press coverage

My research has been mentioned in various media and forums. Here are a few selected articles: