Coarse-to-Fine Knowledge Selection for Document Grounded Dialogs

Understand

Multi-document grounded dialogue systems (DGDS) belong to a class of conversational agents that answer users' requests by finding supporting knowledge from a collection of documents.

• Most previous studies aim to improve the knowledge retrieval model or propose more effective ways to incorporate external knowledge into a parametric generation model.
• These methods, however, focus on retrieving knowledge from mono-granularity language units (e.g.
• passages, sentences, or spans in documents), which is not enough to effectively and efficiently capture precise knowledge in long documents.