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

arXiv: https://arxiv.org/abs/2307.00866 · HTML: https://mlsanity.com/paper/2307.00866/

## 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 (most cited first, 19 of 19)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://mlsanity.com/paper/2104.09864/) (2021)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Get To The Point: Summarization with Pointer-Generator Networks](https://mlsanity.com/paper/1704.04368/) (2017)
- [Circle Loss: A Unified Perspective of Pair Similarity Optimization](https://mlsanity.com/paper/2002.10857/) (2020)
- [Document-level Relation Extraction as Semantic Segmentation](https://mlsanity.com/paper/2106.03618/) (2021)
- [SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents](https://mlsanity.com/paper/2305.13040/) (2023)
- [Improving Multi-turn Dialogue Modelling with Utterance ReWriter](https://mlsanity.com/paper/1906.07004/) (2019)
- [Improving Coreference Resolution by Learning Entity-Level Distributed Representations](https://mlsanity.com/paper/1606.01323/) (2016)
- [GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue](https://mlsanity.com/paper/1909.12086/) (2019)
- [Incomplete Utterance Rewriting as Semantic Segmentation](https://mlsanity.com/paper/2009.13166/) (2020)
- [PaCE: Unified Multi-modal Dialogue Pre-training with Progressive and Compositional Experts](https://mlsanity.com/paper/2305.14839/) (2023)
- [SARG: A Novel Semi Autoregressive Generator for Multi-turn Incomplete Utterance Restoration](https://mlsanity.com/paper/2008.01474/) (2020)
- [Semantic Role Labeling Guided Multi-turn Dialogue ReWriter](https://mlsanity.com/paper/2010.01417/) (2020)
- [Global Pointer: Novel Efficient Span-based Approach for Named Entity Recognition](https://mlsanity.com/paper/2208.03054/) (2022)
- [Deep Retrieval-Based Dialogue Systems: A Short Review](https://mlsanity.com/paper/1907.12878/) (2019)

## Built on by (most cited first, 9 of 9)

- [MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning](https://mlsanity.com/paper/2309.07915/) (2023)
- [GATEAU: Selecting Influential Samples for Long Context Alignment](https://mlsanity.com/paper/2410.15633/) (2024)
- [A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks](https://mlsanity.com/paper/2510.05608/) (2025)
- [Self-Explanation Prompting Improves Dialogue Understanding in Large Language Models](https://mlsanity.com/paper/2309.12940/) (2023)
- [Improving the Robustness of Distantly-Supervised Named Entity Recognition via Uncertainty-Aware Teacher Learning and Student-Student Collaborative Learning](https://mlsanity.com/paper/2311.08010/) (2023)
- [Multi-Granularity Information Interaction Framework for Incomplete Utterance Rewriting](https://mlsanity.com/paper/2312.11945/) (2023)
- [Mitigating Language-Level Performance Disparity in mPLMs via Teacher Language Selection and Cross-lingual Self-Distillation](https://mlsanity.com/paper/2404.08491/) (2024)
- [Incomplete Utterance Rewriting with Editing Operation Guidance and Utterance Augmentation](https://mlsanity.com/paper/2503.16043/) (2025)
- [Two-stage Incomplete Utterance Rewriting on Editing Operation](https://mlsanity.com/paper/2503.16063/) (2025)

## 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.