DIALKI: Knowledge Identification in Conversational Systems through Dialogue-Document Contextualization
Zeqiu Wu, Bo-Ru Lu, Hannaneh Hajishirzi, Mari Ostendorf · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · 2021
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.