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This paper describes our competing system to enter the MEDIQA-2019 competition.
A question-entailment approach to question answering
Asma Ben Abacha and Dina Demner-Fushman. 2019 · 1901
Earlier work this paper cites.
Multi-task deep neural networks for natural language understanding
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. 2019b · 1901
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Scibert: Pretrained contextualized embeddings for scientific text
Iz Beltagy, Arman Cohan, and Kyle Lo. 2019 · 1903
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Multitask learning
Rich Caruana. 1997 · 1997
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Representation learning using multi-task deep neural networks for semantic classification and information retrieval
Xiaodong Liu, Jianfeng Gao, Xiaodong He, Li Deng, Kevin Duh, and Ye-Yi Wang. 2015 · 2015
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Lessons from natural language inference in the clinical domain
Alexey Romanov and Chaitanya Shivade. 2018 · 2018
Cited alongside, same era.
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. 2019a
Cited in the paper.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Later among the works it cites.
Overview of the mediqa 2019 shared task on textual inference, question entailment and question answering
Asma Ben Abacha, Chaitanya Shivade, and Dina Demner-Fushman. 2019 · 2019
Closest in time.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
Closest in time.
Multi-task learning with sample re-weighting for machine reading comprehension
Yichong Xu, Xiaodong Liu, Yelong Shen, Jingjing Liu, and Jianfeng Gao. 2019 · 2019
Closest in time.
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