DIALKI: Knowledge Identification in Conversational Systems through Dialogue-Document Contextualization

09/10/2021
by   Zeqiu Wu, et al.
0

Identifying relevant knowledge to be used in conversational systems that are grounded in long documents is critical to effective response generation. We introduce a knowledge identification model that leverages the document structure to provide dialogue-contextualized passage encodings and better locate knowledge relevant to the conversation. An auxiliary loss captures the history of dialogue-document connections. We demonstrate the effectiveness of our model on two document-grounded conversational datasets and provide analyses showing generalization to unseen documents and long dialogue contexts.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset