A General Survey on Attention Mechanisms in Deep Learning

Attention is an important mechanism that can be employed for a variety of deep learning models across many different domains and tasks. Additionally, the various measures for evaluating attention models are reviewed, and methods to characterize the structure of attention models based on the proposed framework are discussed.

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• 1 This survey provides an overview of the most important attention mechanisms proposed in the literature.
• 2 The various attention mechanisms are explained by means of a framework consisting of a general attention model, uniform notation, and a comprehensive taxonomy of attention mechanisms.
• 3 Additionally, the various measures for evaluating attention models are reviewed, and methods to characterize the structure of attention models based on the proposed framework are discussed.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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