A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers

@article{Chen2022AUA,
  title={A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers},
  author={Yuzhong Chen and Yu Du and Zhe Xiao and Lin Zhao and Lu Zhang and David Weizhong Liu and Dajiang Zhu and Tuo Zhang and Xintao Hu and Tianming Liu and Xi Jiang},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.11073}
}
Vision transformer (ViT) and its variants have achieved remarkable successes in various visual tasks. The key characteristic of these ViT models is to adopt different aggregation strategies of spatial patch information within the artificial neural networks (ANNs). However, there is still a key lack of unified representation of different ViT architectures for systematic understanding and assessment of model representation performance. Moreover, how those well-performing ViT ANNs are similar to… 

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