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arXiv · 1907.10136

Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations

Vinayshekhar Bannihatti Kumar·Ashwin Srinivasan·Aditi Chaudhary·James Route·Teruko Mitamura·Eric Nyberg
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Abstract

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.

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Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary, James Route, Teruko Mitamura, Eric Nyberg. 2019-07-23. Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations. https://arxiv.org/abs/1907.10136

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