可解释性
计算机科学
突出
数据科学
人工智能
分类学(生物学)
人工神经网络
深层神经网络
机器学习
管理科学
植物
生物
经济
作者
ChaudhariSneha,MithalVarun,PolatkanGungor,RamanathRohan
出处
期刊:ACM Transactions on Intelligent Systems and Technology
[Association for Computing Machinery]
日期:2021-10-22
卷期号:12 (5): 1-32
被引量:232
摘要
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.
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