Tianchen Zhao 赵天辰 (Ziu Tinsan)

Phd. Student at Tsinghua University

Tsinghua University

Biography

Tianchen Zhao is a Phd. student in NICS-EFC Lab at Dept. EE, Tsinghua University, supervised by Prof. Yu Wang and Dr. Xuefei Ning. He got his bachelor and master degree in the Dept. EE Beihang University in 2020 and 2023. His primary research focus is efficient deep learning and software-hardware co-optimization.

News

[2025-02] Join ByteDance as a research intern.
[2025-01] Our paper ViDiT-Q is accepted at ICLR25
[2024-12] Give a talk at TigerLab at the University of WaterLoo about recent diffusion quantization research.
[2024-12] Participate in a talk given by the NICS-EffAlg group at AI Time.
[2024-07] Our paper MixDQ is accepted at ECCV24
[2024-03] Our paper FlashEval is accepted at CVPR24
[2023-12] One co-authored paper is accepted at DATE24
[2023-09] Give a talk at TechBeat about our work about Efficient 3D Perception.
[2023-09] Officially become a member of NICS-EFC Lab, starting my Phd. program.
[2023-07] Our paper Ada3D is accepted at ICCV23, check the Project Page.
[2023-05] Join Infinigence as a research intern.

Interests

Efficient Deep Learning
Computer Vision

Education

PhD in Electrical Engineering, 2023
Tsinghua University
MS in Electrical Engineering, 2020
Beihang University
BSc in Electrical Engineering, 2016
Beihang University

Publications

[ICLR25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

We introduce ViDiT-Q, a quantization method specialized for diffusion transformers. For popular large-scale models (e.g., open-sora, Latte, Pixart-α, Pixart-Σ) for the video and image generation task, ViDiT-Q could achieve W8A8 quantization without metric degradation, and W4A8 without notable visual quality degradation.

Tianchen Zhao, Tongcheng Fang, Haofeng Huang, Enshu Liu, Rui Wan, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang