HAQ-ViT: A hardware-aware post-training quantization for efficient vision transformer inference

Shiqi Zhao, Zhengjie Wang, Heng Sun, Sibo Wang, Zihan Chen, Changzeng Fu, Jie Yang and Mohamad Sawan

Article (2026)

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Department:	Department of Electrical Engineering
Funders:	National Natural Science Foundation of China, Hebei Natural Science Foundation, Fundamental Research Funds for the Central Universities
Grant number:	62404037, F2024501017, Z2024-043
PolyPublie URL:	https://publications.polymtl.ca/76019/
Journal Title:	Knowledge-Based Systems (vol. 342)
Publisher:	Elsevier BV
DOI:	10.1016/j.knosys.2026.115830
Official URL:	https://doi.org/10.1016/j.knosys.2026.115830
Date Deposited:	07 Apr 2026 15:26
Last Modified:	07 Apr 2026 15:26

Cite in APA 7:	Zhao, S., Wang, Z., Sun, H., Wang, S., Chen, Z., Fu, C., Yang, J., & Sawan, M. (2026). HAQ-ViT: A hardware-aware post-training quantization for efficient vision transformer inference. Knowledge-Based Systems, 342, 115830 (14 pages). https://doi.org/10.1016/j.knosys.2026.115830
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