In a multi-turn knowledge-grounded dialog, the difference between the knowledge selected at different turns usually provides potential clues to knowledge selection, which has been largely neglected in previous research. In this paper, we propose a difference-aware knowledge selection method. It first computes the difference between the candidate knowledge sentences provided at the current turn and those chosen in the previous turns. Then, the differential information is fused with or disentangled from the contextual information to facilitate final knowledge selection. Automatic, human observational, and interactive evaluation shows that our method is able to select knowledge more accurately and generate more informative responses, significantly outperforming the state-of-the-art baselines. The codes are available at https://github.com/chujiezheng/DiffKS.

中文翻译：

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基于知识的对话生成的差异感知知识选择

在多轮基于知识的对话中，不同轮选择的知识之间的差异通常为知识选择提供了潜在的线索，而这在以前的研究中被很大程度上忽略了。在本文中，我们提出了一种差异感知知识选择方法。它首先计算当前回合提供的候选知识句子与前一回合选择的候选知识句子之间的差异。然后，差分信息与上下文信息融合或分离，以促进最终的知识选择。自动、人工观察和交互式评估表明，我们的方法能够更准确地选择知识并生成更多信息响应，显着优于最先进的基线。代码可在 https://github 上获得。