UPDF AI

An Attentive Survey of Attention Models

S. Chaudhari,Gungor Polatkan,R. Ramanath,Varun Mithal

2019 · DOI: 10.1145/3465055
ACM Transactions on Intelligent Systems and Technology · 707 Citations

TLDR

A taxonomy that groups existing techniques into coherent categories in attention models is proposed, and how attention has been used to improve the interpretability of neural networks is described.

Abstract

Attention Model has now become an important concept in neural networks that has been researched within diverse application domains. This survey provides a structured and comprehensive overview of the developments in modeling attention. In particular, we propose a taxonomy that groups existing techniques into coherent categories. We review salient neural architectures in which attention has been incorporated and discuss applications in which modeling attention has shown a significant impact. We also describe how attention has been used to improve the interpretability of neural networks. Finally, we discuss some future research directions in attention. We hope this survey will provide a succinct introduction to attention models and guide practitioners while developing approaches for their applications.