Final-year AI undergrad at HKBU | Exploring (M)LLM, Optimization, and Visual Generation
My research focuses on (M)LLM and optimization, particularly in understanding the complex phenomena of deep learning systems. I aim to develop more robust and general techniques through empirical analysis and optimization. I enjoy exploring various scenarios to conduct interesting analyses and improvements, even if it involves a lot of trial and error. This process has taught me a great deal. I plan to share meaningful insights and findings through a blog in the future. Stay tuned for updates!
I am also open to interesting research opportunities. If you are interested in collaborating with me, please feel free to contact me:
Co-authored paper "MergeVQ" accepted at CVPR 2025. Congrats to all!
Jan 1, 2025: Happy New Year! Thanks to all collaborators and friends.
Aug 23, 2024: Invited to serve as a Reviewer for ICLR 2025 in Singapore.
Our team is committed to advancing the analysis and optimization of complex deep learning techniques.
Revolutionize LLM and Diffusion Model Algorithms/Frameworks with Princeton University & Peking University.
