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Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations by Kumar, Vinayshekhar Bannihatti; Srinivasan, Ashwin; Chaudhary, Aditi; Route, James; Mitamura, Teruko; Nyberg, Eric is a scholarly article available to read on EtoBox.

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This paper presents the submissions by Team Dr.Quad to the ACL-BioNLP 2019 shared task on Textual Inference and Question Entailment in the Medical Domain. Our system is based on the prior work Liu et al. (2019) which uses a multi-task objective function for textual entailment. In this work, we explore different strategies for generalizing state-of-the-art language understanding models to the specialized medical domain. Our results on the shared task demonstrate that incorporating domain knowledge through data augmentation is a powerful strategy for addressing challenges posed by specialized domains such as medicine.

Author

Kumar, Vinayshekhar Bannihatti; Srinivasan, Ashwin; Chaudhary, Aditi; Route, James; Mitamura, Teruko; Nyberg, Eric

Published

2019

Language

EN