# Understanding Attention: In Minds and Machines

arXiv: https://arxiv.org/abs/2012.02659 · HTML: https://mlsanity.com/paper/2012.02659/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2020.

## Built on by (most cited first, 1 of 1)

- [Improved Anomaly Detection by Using the Attention-Based Isolation Forest](https://mlsanity.com/paper/2210.02558/) (2022)

## Abstract (arXiv)

Attention is a complex and broad concept, studied across multiple disciplines spanning artificial intelligence, cognitive science, psychology, neuroscience, and related fields. Although many of the ideas regarding attention do not significantly overlap among these fields, there is a common theme of adaptive control of limited resources. In this work, we review the concept and variants of attention in artificial neural networks (ANNs). We also discuss the origin of attention from the neuroscience point of view parallel to that of ANNs. Instead of having seemingly disconnected dialogues between varied disciplines, we suggest grounding the ideas on common conceptual frameworks for a systematic analysis of attention and towards possible unification of ideas in AI and Neuroscience.