| CARVIEW |
I'm a forth 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 with intelligent physical agents, and deploy them in the real world. To that end, I've explored the area of real-world reinforcement learning, and looked into the dynamics of diffusion models.
I'm fortunate to be advised by Professor Huazhe Xu. I also have the honor of collaborating with professor C. Karen Liu and professor Shuran Song during my visit during my visit at the Movement Lab of Stanford University.
I'm always curious and fascinated by the intersection of different fields, feel free to reach me out for any discussions! I love to watch movies, recently, I have been studying video filming, here are some of my works.
Updates
- Nov. 2025 Robot Trains Robot has been accepted to CoRL 2025!
- Mar. 2025 I finished the visit and come back to Tsinghua! Chat is always welcome!
- Feb. 2025 Two papers Stem-Ob and DenseMatcher has been accepted to ICLR 2025 as spotlight!
- 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
Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
Kaizhe Hu*,
Haochen Shi*,
Yao He,
Weizhuo Wang,
C. Karen Liu†,
Shuran Song†
CoRL 2025, Poster, Oct. 2025
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ArXiv •
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Video •
Twitter
Stem-Ob: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion
Kaizhe Hu*,
Zihang Rui*,
Yao He,
Yuyao Liu,
Pu Hua,
Huazhe Xu
ICLR 2025, Spotlight (Top 5.1%) , Nov. 2024
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ArXiv •
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Video •
Twitter
DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from One Demo
Junzhe Zhu*,
Yuanchen Ju*,
Junyi Zhang,
Muhan Wang,
Zhecheng Yuan,
Kaizhe Hu,
Huazhe Xu
ICLR 2025, Spotlight (Top 5.1%) , Dec 2024
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ArXiv •
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Data •
Twitter
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
Yongyuan Liang,
Tingqiang Xu,
Kaizhe Hu,
Guangqi Jiang,
Furong Huang,
Huazhe Xu
Neurips 2024, Poster, July 2024
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ArXiv •
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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, Poster, Jan. 2024
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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
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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
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ArXiv •
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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
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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
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ArXiv •
Code