Scholar
Jiawei Fan
Google Scholar ID: 7H674NUAAAAJ
Intel Labs China
Deep Learning
Computer Vision
Model Compression
Deep Learning Acceleration
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Citations & Impact
All-time
Citations
26
H-index
2
i10-index
1
Publications
6
Co-authors
5
list available
Contact
Email
jiawei.fan@intel.com
CV
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GitHub
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Publications
2 items
SliderQuant: Accurate Post-Training Quantization for LLMs
2026
Cited
0
Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
2025
Cited
0
Resume (English only)
Academic Achievements
ICML 2025: Proposed Morse, a universal diffusion acceleration framework applicable to any diffusion model.
NeurIPS 2024 (first author): Introduced ScaleKD, the first work to transfer scalability of pre-trained ViTs to diverse student architectures.
NeurIPS 2023 (first author): Proposed Af-DCD, an augmentation-free dense contrastive distillation framework for efficient semantic segmentation.
ACCV 2022 (co-first author): Developed TCVM for self-supervised video representation learning; received Best Paper Award Honorable Mention (Oral).
ACM MM 2022 (first author): Proposed DTR, a parameter-free information bottleneck regularization framework for action recognition.
ICPR 2022 (first author): Proposed Episodic Projection Network for out-of-distribution detection in few-shot learning.
Ranked 7th in the 3rd Person in Context Workshop at CVPR 2021.
Recipient of Intel Labs China DRA Award (2023), MEGVII Outstanding Intern Award (2022), and BUPT First-Class Scholarship (2021).
Co-authors
5 total
Anbang Yao (姚安邦)
Research Director, Intel Labs China
Meina Song
Professor of Computer Science, Beijing University of Posts and Telecommunications
Co-author 3
Chao Li
Intel Labs China
Zhonghong Ou
School of Computer Science, Beijing University of Posts and Telecommunications (BUPT), China
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