McQueen: a Benchmark for Multimodal Conversational Query Rewrite

Yifei Yuan, Chen Shi, Runze Wang, Liyi Chen, Feijun Jiang, Yuan You, Wai Lam

Abstract
The task of query rewrite aims to convert an in-context query to its fully-specified version where ellipsis and coreference are completed and referred-back according to the history context. Although much progress has been made, less efforts have been paid to real scenario conversations that involve drawing information from more than one modalities. In this paper, we propose the task of multimodal conversational query rewrite (McQR), which performs query rewrite under the multimodal visual conversation setting. We collect a large-scale dataset named McQueen based on manual annotation, which contains 15k visual conversations and over 80k queries where each one is associated with a fully-specified rewrite version. In addition, for entities appearing in the rewrite, we provide the corresponding image box annotation. We then use the McQueen dataset to benchmark a state-of-the-art method for effectively tackling the McQR task, which is based on a multimodal pre-trained model with pointer generator. Extensive experiments are performed to demonstrate the effectiveness of our model on this task.
Anthology ID:
2022.emnlp-main.320
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:
4834–4844
Language:
URL:
https://aclanthology.org/2022.emnlp-main.320
DOI:
10.18653/v1/2022.emnlp-main.320
Bibkey:
Cite (ACL):
Yifei Yuan, Chen Shi, Runze Wang, Liyi Chen, Feijun Jiang, Yuan You, and Wai Lam. 2022. McQueen: a Benchmark for Multimodal Conversational Query Rewrite. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 4834–4844, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
McQueen: a Benchmark for Multimodal Conversational Query Rewrite (Yuan et al., EMNLP 2022)
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PDF:
https://preview.aclanthology.org/ingest-acl-2023-videos/2022.emnlp-main.320.pdf
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