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05/24/2023
BinaryViT: Towards Efficient and Accurate Binary Vision Transformers
Vision Transformers (ViTs) have emerged as the fundamental architecture ...
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05/11/2023
Patch-wise Mixed-Precision Quantization of Vision Transformer
As emerging hardware begins to support mixed bit-width arithmetic comput...
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12/16/2022
RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers
Post-training quantization (PTQ), which only requires a tiny dataset for...
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09/13/2022
PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers
Data-free quantization can potentially address data privacy and security...
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07/04/2022
I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference
Vision Transformers (ViTs) have achieved state-of-the-art performance on...
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03/04/2022
Patch Similarity Aware Data-Free Quantization for Vision Transformers
Vision transformers have recently gained great success on various comput...
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04/28/2020
Angle-based Search Space Shrinking for Neural Architecture Search
In this work, we present a simple and general search space shrinking met...
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02/27/2019
Cluster Regularized Quantization for Deep Networks Compression
Deep neural networks (DNNs) have achieved great success in a wide range ...
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02/27/2019
Multi-loss-aware Channel Pruning of Deep Networks
Channel pruning, which seeks to reduce the model size by removing redund...
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05/29/2018
