Chao Du

Chao Du

Senior Research Scientist · Sea AI Lab, Singapore

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I am a senior research scientist at Sea AI Lab. I received my Ph.D. from Tsinghua University, where I was advised by Prof. Jun Zhu, and my undergraduate degree from the Yao Class at Tsinghua University.

I work on machine learning. My research goal is to understand what intelligence is and how it arises, and to answer these questions from the perspective of probability and statistics. Currently, I focus on developing probabilistic methods for generative modeling from first principles, seeking to explain how structured representations and knowledge emerge from data.

We are hiring Research Scientists and Research Interns to work on generative models (e.g., diffusion models, LLMs). Feel free to reach out if you are interested.

Selected Publications

Generative Modeling
Nonparametric Data Attribution for Diffusion Models
Yutian Zhao*, Chao Du*, Xiaosen Zheng, Tianyu Pang, Min Lin
Preprint, 2025
Paper Code
On Memorization in Diffusion Models
Xiangming Gu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Ye Wang
Transactions on Machine Learning Research (TMLR), 2025
Paper Code
Scaling up Masked Diffusion Models on Text
Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, Chongxuan Li
International Conference on Learning Representations (ICLR), Singapore, 2025
Paper Code
Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows
Chao Du, Tianbo Li, Tianyu Pang, Shuicheng Yan, Min Lin
International Conference on Machine Learning (ICML), Hawaii, USA, 2023
Paper Code Slides Poster
Reinforcement Learning
Continual Reinforcement Learning by Planning with Online World Models
Zichen Liu, Guoji Fu, Chao Du, Wee Sun Lee, Min Lin
International Conference on Machine Learning (ICML), Vancouver, Canada, 2025
Paper Code
Locality Sensitive Sparse Encoding for Learning World Models Online
Zichen Liu, Chao Du, Wee Sun Lee, Min Lin
International Conference on Learning Representations (ICLR), Vienna, Austria, 2024
Paper Code in Appendix
RL for Language Models
Reinforcing General Reasoning Without Verifiers
Xiangxin Zhou, Zichen Liu, Anya Sims, Haonan Wang, Tianyu Pang, Chongxuan Li, Liang Wang, Min Lin, Chao Du
International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, 2026
Paper Code
Sample-Efficient Alignment for LLMs
Zichen Liu, Changyu Chen, Chao Du, Wee Sun Lee, Min Lin
Preprint, 2024
Paper Code

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