Ashwin Srinivasan


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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
Proceedings of the 18th BioNLP Workshop and Shared Task

This paper presents the submissions by TeamDr.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 specialized domains such as medicine.


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USP-IBM-1 and USP-IBM-2: The ILP-based Systems for Lexical Sample WSD in SemEval-2007
Lucia Specia | Maria das Graças | Volpe Nunes | Ashwin Srinivasan | Ganesh Ramakrishnan
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)