Zhan Ling

I am currently a Research Scientist at ByteDance, focusing on enhancing the reasoning capabilities of LLMs. I have received my Ph.D. at UC San Diego , advised by Prof. Hao Su. I have previously interned at Qualcomm and X, the Moonshot Factory. Before starting my Ph.D., I received my B.E. in computer science from Yao Class at Tsinghua University.

Research interest

My long-term research interests lie in developing intelligent agents that can solve challenging problems and continually improve through interactions. I have extensively explored diverse areas such as imitation learning, reinforcement learning, robotics, and reasoning. Currently, my primary goal is to create an LLM/VLM-based reasoning agent capable of achieving superhuman performance on challenging problems, such as solving advanced math and coding problems.

Publications and preprints

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

ActPlan-1K: Benchmarking the Procedural Planning Ability of Visual Language Models in Household Activities
Ying Su, Zhan Ling, Haochen Shi, Cheng Jiayang, Yauwai Yim, Yangqiu Song
Empirical Methods in Natural Language Processing (EMNLP), 2024, Main
arXiv / code

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

Approximate Convex Decomposition for 3D Meshes with Collision-Aware Concavity and Tree Search
Xinyue Wei*, Minghua Liu*, Zhan Ling, Hao Su
ACM Transactions on Graphics(TOG), Proceedings of SIGGRAPH (Journal Track), 2022
arXiv / code / website / video

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, ICRA, AISTATS, ACCV.
Program Committee: AAAI.
Journal Reviewer: T-RO, RA-L.