I'm a third year Computer Science PhD student at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University. Before that, I received my Bachelor's Degree at the Department of Electronic Engineering, Tsinghua University.
My primary interest of research is on combining knowledge of pretrained generative models to intelligent agents that can serve human. To that end, I've explored the area of embodied AI, reinforcement learning, and generative models.
I'm fortunate to be advised by Professor Huazhe(Harry) Xu. I'm currently visiting professor C. Karen Liu's lab at Stanford University.
Updates
- Oct. 2024 Make-An-Agent has been accpeted to Neurips 2024 AFM workshop as Oral representation!
- Sept. 2024 Make-An-Agent has been accpeted to Neurips 2024.
- Aug. 2024 I started my visiting at Stanford University! Advised by Prof. C. Karen Liu.
- July 2024 Robo-ABC has been accpeted to ECCV 2024.
- May 2024 Rethinking Transformers in Solving POMDPs has been accpeted to ICML 2024.
- Jan. 2024 Uni-O4 has been accpeted to ICLR 2024 with a high score of 6688!
- Sept. 2023 LfVoid and RL-ViGen has been accpeted to Neurips 2023.
- Jan. 2023 Decision Transformer under Random Frame Droping (DeFog) has been accpeted to ICLR 2023.
- Jan. 2023 Extraneousness-aware Imitation Learning (EIL) has been accpeted to ICRA 2023.
- Sept. 2022 I started my PhD at Tsinghua University, advised by Prof. Huazhe Xu
Research
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
Yongyuan Liang,
Tingqiang Xu,
Kaizhe Hu,
Guangqi Jiang,
Furong Huang,
Huazhe Xu
Conference on Neural Information Processing Systems (Neurips) 2024, Poster; AFM Workshop, Oral, Jul. 2024
Website •
ArXiv •
Code •
Twitter •
Models&Dataset
Robo-ABC: Affordance Generalization Beyond Categories via Semantic Correspondence for Robot Manipulation
Yuanchen Ju*,
Kaizhe Hu*,
Guowei Zhang,
Gu Zhang,
Mingrun Jiang,
Huazhe Xu
European Conference on Computer Vision (ECCV) 2024, Jan. 2024
Website •
ArXiv •
Code •
Twitter
Rethinking Transformers in Solving POMDPs
Chenhao Lu,
Ruizhe Shi*,
Yuyao Liu*,
Kaizhe Hu,
Simon Shaolei Du,
Huazhe Xu
The International Conference on Machine Learning (ICML) 2024, Poster, May
ArXiv •
Code
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
Lei Kun,
Zhengmao He*,
Chenhao Lu*,
Kaizhe Hu,
Gao Yang,
Huazhe Xu
International Conference on Learning Representations (ICLR) 2024, Poster, Nov. 2023
Website •
ArXiv •
Code •
Twitter
LfVoid: Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning?
Jialu Gao*,
Kaizhe Hu*,
Guowei Xu,
Huazhe Xu
Conference on Neural Information Processing Systems (Neurips) 2023, Poster, Jul. 2023
Website •
ArXiv •
Twitter
RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization
Zhecheng Yuan*,
Sizhe Yang*,
Pu Hua,
Can Chang,
Kaizhe Hu,
Xiaolong Wang,
Huazhe Xu
Conference on Neural Information Processing Systems (Neurips) 2023 Datasets and Benchmarks Track, Poster, Jul. 2023
Website •
ArXiv •
Code
DeFog: Decision Transformer under Random Frame Dropping
Kaizhe Hu*,
Ray Chen Zheng* ,
Yang Gao,
Huazhe Xu
International Conference on Learning Representations (ICLR) 2023, Poster, Mar. 2023
Website •
ArXiv •
Code
EIL: Extraneousness-Aware Imitation Learning
Ray Chen Zheng*,
Kaizhe Hu*,
Zhecheng Yuan,
Boyuan Chen,
Huazhe Xu,
International Conference on Robotics and Automation (ICRA) 2023, Poster, Oct. 2022
Website •
ArXiv •
Code