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08/25/2023
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Large language models (LLMs) have revolutionized natural language proces...
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06/09/2023
Spatial Re-parameterization for N:M Sparsity
This paper presents a Spatial Re-parameterization (SpRe) method for the ...
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05/29/2023
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers
Token compression aims to speed up large-scale vision transformers (e.g....
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05/14/2023
MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization
Arbitrary bit-width network quantization has received significant attent...
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12/26/2022
SMMix: Self-Motivated Image Mixing for Vision Transformers
CutMix is a vital augmentation strategy that determines the performance ...
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05/23/2022
Super Vision Transformer
We attempt to reduce the computational costs in vision transformers (ViT...
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03/08/2022
Coarse-to-Fine Vision Transformer
Vision Transformers (ViT) have made many breakthroughs in computer visio...
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01/30/2022
Optimizing Gradient-driven Criteria in Network Sparsity: Gradient is All You Need
Network sparsity receives popularity mostly due to its capability to red...
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09/09/2021