Kaiwen Zheng (郑凯文)

I’m a third-year Ph.D. student at the Department of Computer Science and Technology, Tsinghua University, advised by Prof. Jun Zhu. Before that, I received my B.E. degree from the same department at Tsinghua University in 2022. In the summer of 2024, I was honored to have an internship at NVIDIA Deep Imagination Research in the San Francisco Bay Area.

My research focuses on developing principled, insightful, scalable, efficient and effective training/inference techniques for deep generative models, with a particular emphasis on diffusion-related models.

Selected Publications & Preprints [full list]

(*) denotes equal contribution; (†) denotes corresponding author

arXiv

Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator

Kaiwen Zheng , Yongxin Chen , Huayu Chen, Guande He, Ming-Yu Liu^†, Jun Zhu^†, and Qinsheng Zhang

arXiv preprint arXiv:2503.01103, 2025

PDF Website
ICLR

Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Kaiwen Zheng , Yongxin Chen, Hanzi Mao, Ming-Yu Liu^†, Jun Zhu^†, and Qinsheng Zhang

In The Thirteenth International Conference on Learning Representations, 2025

Top 5%

PDF Blog
ICLR

Diffusion Bridge Implicit Models

Kaiwen Zheng^*, Guande He^*, Jianfei Chen, Fan Bao, and Jun Zhu^†

In The Thirteenth International Conference on Learning Representations, 2025

PDF Code
arXiv

Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models

Fan Bao, Chendong Xiang^*, Gang Yue^*, Guande He^* , Hongzhou Zhu^*, Kaiwen Zheng^*, Min Zhao^* , Shilong Liu^* , Yaole Wang^*, and Jun Zhu^†

Technical Report, 2024

PDF Website
NeurIPS

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics

Kaiwen Zheng^*, Cheng Lu^*, Jianfei Chen, and Jun Zhu^†

In Advances in Neural Information Processing Systems, 2023

PDF Code Slides Website
ICML

Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs

Kaiwen Zheng^*, Cheng Lu^*, Jianfei Chen, and Jun Zhu^†

In Proceedings of the 40th International Conference on Machine Learning, 2023

PDF Code

Experience

Deep Imagination Research, NVIDIA

Research Intern

2024.06 - 2024.11

Santa Clara, California, USA

Shengshu Technology

Research Intern

2023.03 - 2024.05

Beijing, China

Y-tech, Kuaishou Technology

Engineering Intern

2021.06 - 2021.08

Beijing, China

Miscellaneous

My slides for TSAIL reading group:

Personal

I enjoy playing ping-pong🏓 in my free time. I also watch esports (especially League of Legends) and have a taste for Chinese calligraphy (my piece of the poem 'Qingming' ("清明" in Chinese)).

I am enthusiastic about math since middle school. In high school, I gathered and created a set of interesting math exercises to form a test ([Problems][Answers], in Chinese).