Zeyi Huang
I am a fifth-year PhD student in the Department of Computer Sciences at the University of Wisconsin–Madison, advised by Prof. Yong Jae Lee. Prior to UW–Madison, I obtained my M.S. degree from the Robotics Institute at Carnegie Mellon University, where I worked with Dr. Dong Huang, Prof. Haohan Wang, and Prof. Eric Xing. I received my B.E. degree from Nanjing University of Science and Technology.
I have interned at Microsoft with Yelong Shen; at Meta with Daniel Bolya, Christoph Feichtenhofer, and Miao Liu; and at Adobe with Zongze Wu and Eli Shechtman.
I expect to graduate in Fall 2026 and am seeking full-time research roles.
Research Interests
My research focuses on building more capable and computationally efficient large language models, focusing recently on recurrent Transformer architectures, pre-training, and post-training. LRT introduces cross-token latent recurrence to reduce language-modeling loss at matched training compute, with one forward pass per generated token. LRT with Thought Tokens scales test-time computation through latent thinking steps, offering a parameter-efficient alternative to increasing model depth.
My broader research includes reinforcement learning for selecting from a large set of visual tools (VisTA) and enabling large language models to understand images and videos through structured textual representations (SVG-LLM, VideoMindPalace).