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.
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CITATION STYLE
Li, Z., Li, J., Tang, H., Zhu, K. Q., & Yang, R. (2023). Incomplete Utterance Rewriting by A Two-Phase Locate-and-Fill Regime. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 2731–2745). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-acl.171