Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension

Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li


Abstract
This paper considers the reading comprehension task in which multiple documents are given as input. Prior work has shown that a pipeline of retriever, reader, and reranker can improve the overall performance. However, the pipeline system is inefficient since the input is re-encoded within each module, and is unable to leverage upstream components to help downstream training. In this work, we present RE3QA, a unified question answering model that combines context retrieving, reading comprehension, and answer reranking to predict the final answer. Unlike previous pipelined approaches, RE3QA shares contextualized text representation across different components, and is carefully designed to use high-quality upstream outputs (e.g., retrieved context or candidate answers) for directly supervising downstream modules (e.g., the reader or the reranker). As a result, the whole network can be trained end-to-end to avoid the context inconsistency problem. Experiments show that our model outperforms the pipelined baseline and achieves state-of-the-art results on two versions of TriviaQA and two variants of SQuAD.
Anthology ID:
P19-1221
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2019
Address:
Florence, Italy
Editors:
Anna Korhonen, David Traum, Lluís Màrquez
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2285–2295
Language:
URL:
https://aclanthology.org/P19-1221
DOI:
10.18653/v1/P19-1221
Bibkey:
Cite (ACL):
Minghao Hu, Yuxing Peng, Zhen Huang, and Dongsheng Li. 2019. Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2285–2295, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension (Hu et al., ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/P19-1221.pdf
Code
 huminghao16/RE3QA
Data
SQuADTriviaQA