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://www.aclweb.org/anthology/2020.coling-main.229
DOI:
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http://aclanthology.lst.uni-saarland.de/2020.coling-main.229.pdf