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DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain

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arxiv 1906.04382 v1 pith:CHIOKNXC submitted 2019-06-11 cs.CL

Yichong Xu , Xiaodong Liu , Chunyuan Li , Hoifung Poon , Jianfeng Gao This is my paper · ORCID
classification cs.CL
keywords learningmedicaltransferdomainlanguagenaturalunderstandingmulti-source
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This paper describes our competing system to enter the MEDIQA-2019 competition. We use a multi-source transfer learning approach to transfer the knowledge from MT-DNN and SciBERT to natural language understanding tasks in the medical domain. For transfer learning fine-tuning, we use multi-task learning on NLI, RQE and QA tasks on general and medical domains to improve performance. The proposed methods are proved effective for natural language understanding in the medical domain, and we rank the first place on the QA task.

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