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arXiv · 2210.02223

CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversations

Lin Xu·Qixian Zhou·Jinlan Fu·Min-Yen Kan·See-Kiong Ng
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Abstract

Knowledge-grounded dialog systems need to incorporate smooth transitions among knowledge selected for generating responses, to ensure that dialog flows naturally. For document-grounded dialog systems, the inter- and intra-document knowledge relations can be used to model such conversational flows. We develop a novel Multi-Document Co-Referential Graph (Coref-MDG) to effectively capture the inter-document relationships based on commonsense and similarity and the intra-document co-referential structures of knowledge segments within the grounding documents. We propose CorefDiffs, a Co-referential and Differential flow management method, to linearize the static Coref-MDG into conversational sequence logic. CorefDiffs performs knowledge selection by accounting for contextual graph structures and the knowledge difference sequences. CorefDiffs significantly outperforms the state-of-the-art by 9.5\%, 7.4\%, and 8.2\% on three public benchmarks. This demonstrates that the effective modeling of co-reference and knowledge difference for dialog flows are critical for transitions in document-grounded conversation

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Lin Xu, Qixian Zhou, Jinlan Fu, Min-Yen Kan, See-Kiong Ng. 2022-10-05. CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversations. https://arxiv.org/abs/2210.02223

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