Hi! I am Xiaohui Wang, a third-year undergraduate student majoring in Electronic Information Science and Technology at Fudan University. I am fortunate to be advised by Prof. Tao Chen at the Fudan EDL Lab. I also work closely with Dr. Peng Ye (Postdoc at CUHK MMLab). My research interests lie in Efficient AI, Multi-Modal AI, and Embodied AI.
I am proud to have received the National Scholarship (2022-2023) for my academic achievements, with a GPA of 93/100. I am passionate about exploring ways to enhance AI systems for more efficient and versatile real-world applications.
This summer, I will be joining HKU MMLab as a research intern under the supervision of Prof. Ping Luo. I am excited to work alongside talented researchers.
If you are interested in connecting, collaborating, or discussing ideas, feel free to reach out to me via email. I am also seeking a Ph.D. position for Fall 2026. You can access my CV HERE.
π₯ News
- 2025.05: Β ππ Our work UltraDelta is now on arxivοΌ
- 2025.05: Β ππ I am proud to be named one of the Top 10 Students in the School of Information Science and Technology!
- 2025.05: Β ππ I have received the Fumei Summer Research Scholarship. Many thanks to the Fumei Foundation!
- 2025.03: Β ππ Our work Delta-DCT is now on arxivοΌ
π Honors and Awards
- 2022-2023 National Scholarship
- 2024-2025 Top 10 Student Award at School of Information Science and Technology
- 2025.05 Fumei Summer Research Scholarship (awarded to only 4 students at Fudan University)
- 2023-2024 SCSK Corporation Scholarship
- 2024.09 China Undergraduate Mathematical Contest in Modeling (Second Prize, Shanghai)
π Preprint
Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression
Xiaohui Wang*, Peng Ye*, Chenyu Huang, Shenghe Zheng, Bo Zhang, Lei Bai, Wanli Ouyang, Tao Chenβ
- To break the compression ceiling of delta weights, we analyze the limitations of existing methods in information preservation and model stability, and propose UltraDelta, the first data-free pipeline enabling ultra-efficient delta compression, achieving both ultra-high compression ratios and strong performance without relying on any data.
Seeing Delta Parameters as JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform
Chenyu Huang*, Peng Ye*, Xiaohui Wang, Shenghe Zheng, Biqing Qi, Lei Bai, Wanli Ouyang, Tao Chenβ
- Motivated by the classic JPEG compression, we explore the delta compression from the DCT domain for the first time. We first realize data-free delta compression and further reduce the performance degradation. We propose a framework based on compression in the DCT domain, named DELTA-DCT.
π Education
- 2022.06 - present, Electronic Information Science and Technology, Fudan University. (GPA:93/100, rank: 5/95 in class, 8/295 in school)
Last update in June 2025