mlsanityData to 14 Oct 2026

Mining Clues from Incomplete Utterance: A Query-enhanced Network for Incomplete Utterance Rewriting

arXiv 2307.00866 ↗First posted 3 Jul 2023cs.CL cs.AIcited by 9

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Abstract (arXiv)

Incomplete utterance rewriting has recently raised wide attention. However, previous works do not consider the semantic structural information between incomplete utterance and rewritten utterance or model the semantic structure implicitly and insufficiently. To address this problem, we propose a QUEry-Enhanced Network (QUEEN). Firstly, our proposed query template explicitly brings guided semantic structural knowledge between the incomplete utterance and the rewritten utterance making model perceive where to refer back to or recover omitted tokens. Then, we adopt a fast and effective edit operation scoring network to model the relation between two tokens. Benefiting from proposed query template and the well-designed edit operation scoring network, QUEEN achieves state-of-the-art performance on several public datasets.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 19 of its 31 references that are in the map. First posted on arXiv 3 Jul 2023.

Builds on

19 of 31 references.

References · 19

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7 more
  1. 2019GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialoguecited by 33
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Cited by year

Citing papers per year: 2023: 4; 2024: 2; 2025: 3.

9 papers.