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Sieg at MEDIQA 2019: Multi-task Neural Ensemble for Biomedical Inference and Entailment

Sai Abishek Bhaskar, Rashi Rungta, James Route, Eric Nyberg, Teruko Mitamura
2019 Proceedings of the 18th BioNLP Workshop and Shared Task  
This paper presents a multi-task learning approach to natural language inference (NLI) and question entailment (RQE) in the biomedical domain.  ...  Our final models for the NLI and RQE tasks achieve the 4 th and 2 nd rank on the shared-task leaderboard respectively.  ...  For the current work, we use the Multi-Task Deep Neural Networks for Natural Language Understanding (MT-DNN) introduced in Liu et al. 2019, which demonstrates the effectiveness of multi-task learning by  ... 
doi:10.18653/v1/w19-5049 dblp:conf/bionlp/BhaskarRRNM19 fatcat:2tzkd6nrxvbivfdg5jnjtbycym

Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering

Asma Ben Abacha, Chaitanya Shivade, Dina Demner-Fushman
2019 Proceedings of the 18th BioNLP Workshop and Shared Task  
This paper presents the MEDIQA 2019 shared task organized at the ACL-BioNLP workshop.  ...  MEDIQA 2019 includes three tasks: Natural Language Inference (NLI), Recognizing Question Entailment (RQE), and Question Answering (QA) in the medical domain. 72 teams participated in the challenge, achieving  ...  We would like to thank Sharada Mohanty, CEO and co-founder of AIcrowd, and Yassine Mrabet from the NLM for his support with the CHiQA system.  ... 
doi:10.18653/v1/w19-5039 dblp:conf/bionlp/AbachaSD19 fatcat:fa2z477k7jfitkd6yfgksyrofa