Incomplete Utterance Rewriting by A Two-Phase Locate-and-Fill Regime

Zitong Li, Jiawei Li, Haifeng Tang, Kenny Zhu, Ruolan Yang

Abstract
Rewriting incomplete and ambiguous utterances can improve dialogue models’ understanding of the context and help them generate better results. However, the existing end-to-end models will have the problem of too large search space, resulting in poor quality of rewriting results. We propose a 2-phase rewriting framework which first predicts the empty slots in the utterance that need to be completed, and then generate the part to be filled into each positions. Our framework is simple to implement, fast to run, and achieves the state-of-the-art results on several public rewriting datasets.
Anthology ID:
2023.findings-acl.171
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2731–2745
Language:
URL:
https://aclanthology.org/2023.findings-acl.171
DOI:
10.18653/v1/2023.findings-acl.171
Bibkey:
Cite (ACL):
Zitong Li, Jiawei Li, Haifeng Tang, Kenny Zhu, and Ruolan Yang. 2023. Incomplete Utterance Rewriting by A Two-Phase Locate-and-Fill Regime. In Findings of the Association for Computational Linguistics: ACL 2023, pages 2731–2745, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Incomplete Utterance Rewriting by A Two-Phase Locate-and-Fill Regime (Li et al., Findings 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/add_acl24_videos/2023.findings-acl.171.pdf
PDF Search