Rongzhen Wang (王榕甄)

Biography

I am currently a third-year Ph.D. student in the GSAI-ML Group, Renmin University of China, advised by Prof. Chongxuan Li.

I am interested in optimization and architectural improvements for neural network training.

Previously, I have worked on the theoretical analysis and method design of optimization algorithms and generative models.

* indicates equal contribution

LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models
Fengqi Zhu*, Rongzhen Wang*, Shen Nie, Xiaolu Zhang, Chunwei Wu, Jun Hu, Jun Zhou, Jianfei Chen, Yankai Lin, Ji-Rong Wen, Chongxuan Li
Annual Meeting of the Association for Computational Linguistics (ACL), 2026
[Code] [Model]
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng, Chongxuan Li, Guoqiang Wu
International Conference on Machine Learning (ICML), 2025
[Code] [Slides]
Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization
Rongzhen Wang, Chenyu Zheng, Guoqiang Wu, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
Advances in Neural Information Processing Systems (NeurIPS), 2024
[Slides]

Scaling Diffusion Transformers Efficiently via μP
Chenyu Zheng, Xinyu Zhang, Rongzhen Wang, Wei Huang, Zhi Tian, Weilin Huang, Jun Zhu, Chongxuan Li
Advances in Neural Information Processing Systems (NeurIPS), 2025
[Code] [机器之心]
ControlVideo: Conditional Control for One-shot Text-driven Video Editing and Beyond
Min Zhao, Rongzhen Wang, Fan Bao, Chongxuan Li, Jun Zhu
Science China Information Sciences (SCIS), 2025
[Code] [Project Page]
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li
Advances in Neural Information Processing Systems (NeurIPS), 2024
[Code] [Slides]

I like to take notes :) Here are some of my presentations and notes.

LLM Scaling Laws, 12.2025 [Slides]
Basics of Reinforcement Learning and LLM Alignment, 7.2025 [Slides in Chinese]
A Brief Introduction to Learning Theory, 11.2024 [Slides]
Algorithmic Stability of Bilevel (Stochastic) Gradient Descent, 3.2024 [Slides]
Algorithmic Stability of (Stochastic) Gradient Descent, 12.2023 [Slides]