# Deep Learning Models for Automatic Summarization

arXiv: https://arxiv.org/abs/2005.11988 · HTML: https://mlsanity.com/paper/2005.11988/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2020.

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

- [Extractive Summarization of Call Transcripts](https://mlsanity.com/paper/2103.10599/) (2021)

## Abstract (arXiv)

Text summarization is an NLP task which aims to convert a textual document into a shorter one while keeping as much meaning as possible. This pedagogical article reviews a number of recent Deep Learning architectures that have helped to advance research in this field. We will discuss in particular applications of pointer networks, hierarchical Transformers and Reinforcement Learning. We assume basic knowledge of Seq2Seq architecture and Transformer networks within NLP.