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        <title>CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering</title>
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        <namePart type="given">Junru</namePart>
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    <name type="personal">
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    <name type="personal">
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            <namePart type="given">Chengqing</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering
%A Lu, Junru
%A Pergola, Gabriele
%A Gui, Lin
%A Li, Binyang
%A He, Yulan
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F lu-etal-2020-chime
%X 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.
%R 10.18653/v1/2020.coling-main.229
%U https://aclanthology.org/2020.coling-main.229/
%U https://doi.org/10.18653/v1/2020.coling-main.229
%P 2547-2560

Markdown (Informal)

[CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering](https://aclanthology.org/2020.coling-main.229/) (Lu et al., COLING 2020)

• CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering (Lu et al., COLING 2020)

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.