论文标题
Corefdiffs：文档接地对话中的共同指南和差异知识流
CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversations
论文作者
论文摘要
知识接地的对话系统需要在选择用于生成响应的知识之间进行平稳的过渡，以确保对话框自然流动。对于文档接地的对话系统，可以使用文档内和文档内的知识关系来建模此类对话流。我们开发了一个新颖的多文章共同指南图（CoreF-MDG），以根据常识性和相似性以及在接地文档中知识段的共同参考结构有效地捕获文档间的关系。我们提出了CoreFdiffs，一种共同指南和差分流管理方法，以将静态CoreF-MDG线性化为对话序列逻辑。 Corefdiffs通过考虑上下文图形结构和知识差异序列来执行知识选择。在三个公共基准上，Corefdiffs的表现可以大大优于9.5 \％，7.4 \％和8.2 \％。这表明，对话流的共同参考和知识差异的有效建模对于文档的对话中的过渡至关重要
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
