# A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents

**Authors:** Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, Nazli Goharian  
**arXiv:** [1804.05685](https://arxiv.org/abs/1804.05685)  
**Date:** 2018-04-16  
**Summary page:** https://www.summarizepaper.com/fr/paper/1804.05685v1/

## Abstract

Neural abstractive summarization models have led to promising results in summarizing relatively short documents. We propose the first model for abstractive summarization of single, longer-form documents (e.g., research papers). Our approach consists of a new hierarchical encoder that models the discourse structure of a document, and an attentive discourse-aware decoder to generate the summary. Empirical results on two large-scale datasets of scientific papers show that our model significantly outperforms state-of-the-art models.