CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning
Zeqiu Wu, Yi Luan, Hannah Rashkin, David Reitter, Hannaneh Hajishirzi, Mari Ostendorf, Gaurav Singh Tomar
Abstract
Compared to standard retrieval tasks, passage retrieval for conversational question answering (CQA) poses new challenges in understanding the current user question, as each question needs to be interpreted within the dialogue context. Moreover, it can be expensive to re-train well-established retrievers such as search engines that are originally developed for non-conversational queries. To facilitate their use, we develop a query rewriting model CONQRR that rewrites a conversational question in the context into a standalone question. It is trained with a novel reward function to directly optimize towards retrieval using reinforcement learning and can be adapted to any off-the-shelf retriever. CONQRR achieves state-of-the-art results on a recent open-domain CQA dataset containing conversations from three different sources, and is effective for two different off-the-shelf retrievers. Our extensive analysis also shows the robustness of CONQRR to out-of-domain dialogues as well as to zero query rewriting supervision.- Anthology ID:
- 2022.emnlp-main.679
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10000–10014
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-main.679
- DOI:
- 10.18653/v1/2022.emnlp-main.679
- Cite (ACL):
- Zeqiu Wu, Yi Luan, Hannah Rashkin, David Reitter, Hannaneh Hajishirzi, Mari Ostendorf, and Gaurav Singh Tomar. 2022. CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 10000–10014, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning (Wu et al., EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2022.emnlp-main.679.pdf