Graph-evolving meta-learning for low-resource medical dialogue generation

• Main Authors: LIN, Shuai, ZHOU, Pan, LIANG, Xiaodan, TANG, Jianheng, ZHAO, Ruihui, CHEN, Ziliang, LIN, Liang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9027; https://ink.library.smu.edu.sg/context/sis_research/article/10030/viewcontent/2021_AAAI_Medical__1_.pdf
• Institution: Singapore Management University

Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledge-grounded dialogue systems often require a large number of dialogue instances to learn as they fail to capture the correlations betw...