Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering Gangwoo Kim Hyunjae Kim Jungsoo Park Jaewoo Kangy Korea University fgangwoo kim,
[email protected] fjungsoo park,
[email protected] Conversation History Abstract Title : Leonardo da Vinci One of the main challenges in conversational q Who were his pupils? question answering (CQA) is to resolve the 1 conversational dependency, such as anaphora and ellipsis. However, existing approaches a1 with his pupils Salai and Melzi. do not explicitly train QA models on how to resolve the dependency, and thus these mod- q2 Was he close to his pupils? els are limited in understanding human dia- logues. In this paper, we propose a novel a2 Leonardo's most intimate relationships framework, EXCORD(Explicit guidance on how to resolve Conversational Dependency) q Was he close with anyone else? to enhance the abilities of QA models in com- 3 prehending conversational context. EXCORD Question Rewrite first generates self-contained questions that can be understood without the conversation Self-contained Q history, then trains a QA model with the pairs Was Leonardo da Vinci close with anyone else of original and self-contained questions using q3 other than his pupils Salai and Melzi? a consistency-based regularizer. In our exper- iments, we demonstrate that EXCORD signifi- cantly improves the QA models’ performance Figure 1: An example of the QuAC dataset (Choi et al., by up to 1.2 F1 on QuAC (Choi et al., 2018), 2018). Owing to linguistic phenomena in human con- and 5.2 F1 on CANARD (Elgohary et al., versations, such as anaphora and ellipsis, the current 2019), while addressing the limitations of the question q3 should be understood based on the conver- existing approaches.1 sation history: q1, a1, q2, and a2.