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WHORU: Improving Abstractive Dialogue Summarization with Personal Pronoun Resolution
Version 1
: Received: 5 July 2023 / Approved: 6 July 2023 / Online: 7 July 2023 (10:15:01 CEST)
A peer-reviewed article of this Preprint also exists.
Zhou, T. WHORU: Improving Abstractive Dialogue Summarization with Personal Pronoun Resolution. Electronics 2023, 12, 3091. Zhou, T. WHORU: Improving Abstractive Dialogue Summarization with Personal Pronoun Resolution. Electronics 2023, 12, 3091.
Abstract
With the abundance of conversations happening everywhere, dialogue summarization plays an increasingly important role in the real world. However, dialogues inevitably involve lots of personal pronouns, which hinder the performance of existing dialogue summarization models. This work proposes a framework named WHORU to inject external personal pronoun resolution (PPR) information into abstractive dialogue summarization models. To reduce time and space consumption, we further propose a simple and effective PPR method for the dialogue domain. Experiments demonstrated the superiority of the proposed methods. More importantly, we achieve new SOTA results on SAMSum and AMI datasets.
Keywords
text summarization; abstractive dialogue summarization; personal pronoun resolution
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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