CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering

Junru Lu, Gabriele Pergola, Lin Gui, Binyang Li, Yulan He


Abstract
We introduce CHIME, a cross-passage hierarchical memory network for question answering (QA) via text generation. It extends XLNet introducing an auxiliary memory module consisting of two components: the context memory collecting cross-passage evidences, and the answer memory working as a buffer continually refining the generated answers. Empirically, we show the efficacy of the proposed architecture in the multi-passage generative QA, outperforming the state-of-the-art baselines with better syntactically well-formed answers and increased precision in addressing the questions of the AmazonQA review dataset. An additional qualitative analysis revealed the interpretability introduced by the memory module.
Anthology ID:
2020.coling-main.229
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
2547–2560
Language:
URL:
https://aclanthology.org/2020.coling-main.229
DOI:
10.18653/v1/2020.coling-main.229
Bibkey:
Cite (ACL):
Junru Lu, Gabriele Pergola, Lin Gui, Binyang Li, and Yulan He. 2020. CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering. In Proceedings of the 28th International Conference on Computational Linguistics, pages 2547–2560, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering (Lu et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.229.pdf
Code
 LuJunru/CHIME
Data
AmazonQASQuAD