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Paper · arXiv

Transformer Interpretability from Perspective of Attention and Gradient

Although researchers' attention is more focused on the performance of Transformer models, the interpretation of Transformer can never be ignored. Gradient is widely utilized in Transformer interpretation. From the perspective of attention and gradient, we conduct an in-depth study of Transformer interpretation and propose a method to achieve it by guiding the gradient direction, or more precisely, the attention direction. The method enables more comprehensive interpretation of feature regions, offers detail interpretation, and helps to better understand Transformer mechanism. Leveraging the difference in how Vision Transformer (ViT) and humans perceive images, we alter the class of an ima...

AuthorsYongjin Cui, Xiaohui Fan, Huajun Chen
Primary categorycs.AI
Published12 May 2026
Last updated at source12 May 2026
cs.AI
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