Entity-based SpanCopy for Abstractive Summarization to Improve the Factual Consistency

1Citations
Citations of this article
22Readers
Mendeley users who have this article in their library.

Abstract

Discourse-aware techniques, including entity-aware approaches, play a crucial role in summarization. In this paper, we propose an entity-based SpanCopy mechanism to tackle the entity-level factual inconsistency problem in abstractive summarization, i.e. reducing the mismatched entities between the generated summaries and the source documents. Complemented by a Global Relevance component to identify summary-worthy entities, our approach demonstrates improved factual consistency while preserving saliency on four summarization datasets, contributing to the effective application of discourse-aware methods summarization tasks.

Cite

CITATION STYLE

APA

Xiao, W., & Carenini, G. (2023). Entity-based SpanCopy for Abstractive Summarization to Improve the Factual Consistency. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 70–81). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.codi-1.9

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free