14 citations · 33 across the 11 of their papers we have counts for
5 papers · 1 filter
I&S-ViT: An Inclusive & Stable Method for Pushing the Limit of Post-Training ViTs Quantization
Yunshan Zhong, Jiawei Hu, Mingbao lin +2
Albeit the scalable performance of vision transformers (ViTs), the dense computational costs (training & inference) undermine their position in industrial applications. Post-traini…
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang +7
Large language models (LLMs) have revolutionized natural language processing tasks. However, their practical deployment is hindered by their immense memory and computation requirem…
Spatial Re-parameterization for N:M Sparsity
Yuxin Zhang, Mingbao Lin, Mingliang Xu +2
This paper presents a Spatial Re-parameterization (SpRe) method for the N:M sparsity. SpRe stems from an observation regarding the restricted variety in spatial sparsity of convolu…
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers
Mengzhao Chen, Wenqi Shao, Peng Xu +6
Token compression aims to speed up large-scale vision transformers (e.g. ViTs) by pruning (dropping) or merging tokens. It is an important but challenging task. Although recent adv…
MBQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization
Yunshan Zhong, Yuyao Zhou, Fei Chao +1
Arbitrary bit-width network quantization has received significant attention due to its high adaptability to various bit-width requirements during runtime. However, in this paper, w…