Hi👋 I am Bang Xiao, an undergraduate student major in Computer Science at Shanghai Jiao Tong University, supervised by Cewu Lu and Yonglu Li. I am selected as a member of Zhiyuan Honors Program.
Previously, I was a research intern at GenAI Group, Microsoft Research Asia, supervised by Shaohan Huang and Tengchao Lv.
My research interests broadly span generative models, world models, reinforcement learning, and representation learning. My long-term goal is to build intelligent systems that can truly understand the physical world, and are capable of reasoning and planning.
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Shanghai Jiao Tong UniversityB.S. in Computer Science, Zhiyuan Honors ProgramSep. 2023 - now -
No.1 Middle School Affiliated to Central China Normal UniversityHigh SchoolSep. 2020 - Jun. 2023
Experience
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GenAI Group, Microsoft Research Asia
Superviser: Shaohan Huang and Tengchao LvResearch InternMay. 2025 - Oct. 2025 -
SJTU MVIG Lab
Superviser: Cewu Lu and Yonglu LiResearch InternDec. 2024 - Now -
SJTU EPIC Lab
Superviser: Linfeng ZhangResearch InternAug. 2024 - Dec. 2024
Publications (view all )
Token Pruning for Caching Better: 9$\times$ Acceleration on Stable Diffusion for Free
Evelyn Zhang*, Bang Xiao*, Jiayi Tang, Qianli Ma, Chang Zou, Xuefei Ning, Xuming Hu, Linfeng Zhang# (* equal contribution, # corresponding author)
arXiv preprint 2024
Based on token prune and layer cache technology, we present a new Stable Diffusion acceleration method named dynamics-aware token pruning (DaTo). In the COCO-30k, we observed a 7$\times$ acceleration coupled with a notable FID reduction of 2.17.
Token Pruning for Caching Better: 9$\times$ Acceleration on Stable Diffusion for Free
Evelyn Zhang*, Bang Xiao*, Jiayi Tang, Qianli Ma, Chang Zou, Xuefei Ning, Xuming Hu, Linfeng Zhang# (* equal contribution, # corresponding author)
arXiv preprint 2024
Based on token prune and layer cache technology, we present a new Stable Diffusion acceleration method named dynamics-aware token pruning (DaTo). In the COCO-30k, we observed a 7$\times$ acceleration coupled with a notable FID reduction of 2.17.