Open-Domain Conversational Question Answering with Historical Answers
Hung-Chieh Fang, Kuo-Han Hung, Chen-Wei Huang, Yun-Nung Chen · 2022
Open-domain conversational question answering can be viewed as two tasks: passage retrieval and conversational question answering, where the former relies on selecting candidate passages from a large corpus and the latter requires better understanding of a question with contexts to predict the answers.This paper proposes ConvADR-QA that leverages historical answers to boost retrieval performance and further achieves better answering performance.Our experiments on the benchmark dataset, OR-QuAC, demonstrate that our model outperforms existing baselines in both extractive and generative reader settings, well justifying the effectiveness of historical answers for opendomain conversational question answering.1