Knowledge-grounded dialogue is a task of generating an informative response based on both the dialogue history and external knowledge source. In general, there are two forms of knowledge: manually annotated knowledge graphs and knowledge text from website. From various evaluation viewpoints, each type of knowledge has advantages and downsides. To further distinguish the principles and determinants from the intricate factors, we conduct a thorough experiment and study on the task to answer three essential questions. The questions involve the choice of appropriate knowledge form, the degree of mutual effects between knowledge and the model selection, and the few-shot performance of knowledge. Supported by statistical shreds of evidence, we offer conclusive solutions and sensible suggestions for directions and standards of future research.

翻译：知识驱动对话是基于对话历史与外部知识源生成信息丰富回复的任务。通常，知识存在两种形式：人工标注的知识图谱与网站上的知识文本。从不同评估视角来看，每种知识形式均兼具优势与不足。为从复杂因素中进一步厘清原理与决定性因素，我们针对该任务开展了系统性实验与研究，以回答三个核心问题：如何选择适宜的知识形式、知识与模型选择之间的相互影响程度、以及知识在小样本场景下的表现。基于统计证据，我们为未来研究的方向与标准提供了结论性解决方案与合理建议。