Qunzhong Wang

Qunzhong Wang (王群中)

Hi, I'm Qunzhong Wang. I am currently an undergraduate at the Chinese University of Hong Kong, majoring in Mathematics and Information Engineering.

Prior to my undergraduate studies, I received the gold medal in Chinese Mathematical Olympiad (aka CMO).

My current research interests includes:

Principles of AI Systems backed by Math

Understanding the mathematical principles behind model representation capacity, training dynamics, and generalization.
Leveraging these principles to design better and more scalable architectures, optimizers, training/fine-tuning methods, and regularization techniques.

,

Reinforcement Learning on Large Models

Aligning Large Language Models (LLMs), Vision-Language Models (VLMs), and their derivative Agents with specific human preferences and demands, with techniques like Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning with Verifiable Reward (RLVR).
Exploring robust fine-tuning "recipes" within the RL framework to ensure that pre-trained capabilities are preserved while desired, human-aligned skills are effectively amplified.

I feel incredibly fortunate to have been advised by distinguished scholars: Hong Cheng; Xiangyu Yue; Sotirios Sabanis; Zhuang Liu; Weiyang Liu.

You can view my full resume here.

Email / Scholar / Github

Publications

Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis
Qunzhong Wang, Xiangguo Sun, Hong Cheng
International Conference on Machine Learning (ICML), 2025
arXiv / Paper / Code

A theoretical framework for analyzing graph prompting from a data operation perspective.

VideoSearch Reasoner: Boosting Multimodal Reward Models through Thinking-with-Image Reasoning
Qunzhong Wang, Jie Liu, Jiajun Liang, Yilei Jiang, Yuanxing Zhang, Yaozhi Zheng, Xintao Wang, Pengfei Wan, Xiangyu Yue, Jiaheng Liu
Preprint, Under Review at International Conference on Learning Representations (ICLR) 2026
arXiv / Paper / Code

Boosting multimodal reward models by adding tool invocation capabilities to handle long videos.

ScreenCoder: Advancing Visual-to-Code Generation for Front-End Automation via Modular Multimodal Agents
Yilei Jiang, Yaozhi Zheng, Yuxuan Wan, Qunzhong Wang, Jiaming Han, Michael R. Lyu, Xiangyu Yue. Preprint
arXiv / Paper / Code

End-to-end visual-to-code generation via modular multimodal agents.

Selected Awards

	Talent Development Scholarship, HKGOV (2025)
	Professor Charles K. Kao Research Exchange Scholarships, Chinese University of HK (2025)
	Dean's List, Chinese University of HK (2024, 2025)
	ELITE Stream Scholarship, Chinese University of HK (2024, 2025)
	Mathematical Modeling Contest, Meritorious Winner (2024)
	Soong Ching Ling Scholarship (2023)
	Prof Omar Wing Memorial Scholarship (2023)
	Simon Marais Mathematics Competition, 11th in East Division (2023)
	Admission Scholarship, Chinese University of HK (2023)
	China Physics Olympiad (Provincial), First Prize (2022)
	China Chemistry Olympiad (Provincial), First Prize (2022)
	China Mathematics Olympiad, Gold Medal (2022)

Experiences

2024.04—2024.09

Database Research Group, The Chinese University of Hong Kong

Advised by Prof. Hong Cheng

2024.12—2025.09

Kling AI Technology Department, Kuaishou Technology

Advised by Dr. Xintao Wang

2025.09—Present

Zhuang's Lab, Princeton University

Advised by Prof. Zhuang Liu

Services

	International Conference on Learning Representations (ICLR) Reviewer, 2026
	IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Reviewer, 2026

Talks & Tutorials

A Theoretical Framework for Graph Prompting
ICML 2025 Poster Session. July 2025
Slides

Introducing a theoretical analysis framework of graph prompting methods.

Thinking with Images: A New Paradigm of Multimodal Reward Models
Research Seminar, Kuaishou Technology. December 2025
Slides

Introducing a new paradigm of multimodal reward models with Thinking-with-Image framework.

Blog & Reading Notes

View My Blog