Extractive Summarizer for Scholarly Articles

TL;DR

This paper presents an extractive summarization method for scientific articles that leverages presentation slides as gold standards, improving summary quality measured by ROUGE scores.

Contribution

It introduces a novel labeling approach using presentation slides and deep neural networks to enhance extractive summarization of scholarly papers.

Findings

Achieved at least 4 ROUGE1-Recall points improvement

Utilized presentation slides as gold summaries

Enhanced sentence ranking with neural networks

Abstract

We introduce an extractive method that will summarize long scientific papers. Our model uses presentation slides provided by the authors of the papers as the gold summary standard to label the sentences. The sentences are ranked based on their novelty and their importance as estimated by deep neural networks. Our window-based extractive labeling of sentences results in the improvement of at least 4 ROUGE1-Recall points.