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arXiv · 2101.08426

Content Selection Network for Document-grounded Retrieval-based Chatbots

Yutao Zhu·Jian-Yun Nie·Kun Zhou·Pan Du·Zhicheng Dou
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Abstract

Grounding human-machine conversation in a document is an effective way to improve the performance of retrieval-based chatbots. However, only a part of the document content may be relevant to help select the appropriate response at a round. It is thus crucial to select the part of document content relevant to the current conversation context. In this paper, we propose a document content selection network (CSN) to perform explicit selection of relevant document contents, and filter out the irrelevant parts. We show in experiments on two public document-grounded conversation datasets that CSN can effectively help select the relevant document contents to the conversation context, and it produces better results than the state-of-the-art approaches. Our code and datasets are available at https://github.com/DaoD/CSN.

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Yutao Zhu, Jian-Yun Nie, Kun Zhou, Pan Du, Zhicheng Dou. 2021-01-21. Content Selection Network for Document-grounded Retrieval-based Chatbots. https://arxiv.org/abs/2101.08426

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