Zixuan Wang
Hi! I am Zixuan (子轩) Wang, a third-year Ph.D. student in Electrical and Computer Engineering at Princeton University. I am fortunate to be advised by Prof. Jason D. Lee.
My research interests broadly lie in understanding the foundations of LLMs and deep learning, as well as leveraging both theoretical and empirical explorations to advance the frontiers of deep learning and language modeling.
I did my undergraduate study at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University, also known as Yao Class.
You can contact me at wangzx (at) princeton (dot) edu. My CV is here.
Latest Posts
- SoonNew posts will appear here.
Selected Publications
- Scaling Latent Reasoning via Looped Language Models
- The Power of Power Law: Asymmetry Enables Compositional Reasoning
- Learning Compositional Functions with Transformers from Easy-to-Hard Data
- What Makes a Reward Model a Good Teacher? An Optimization Perspective
- Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought
- Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability