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We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts.
Biobert: pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2019 · 1901
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Probing biomedical embeddings from language models
Qiao Jin, Bhuwan Dhingra, William W Cohen, and Xinghua Lu. 2019 · 1904
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Trec 2006 genomics track overview
William Hersh, Aaron M. Cohen, Phoebe Roberts, and Hari Krishna Rekapalli. 2006 · 2006
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Trec 2007 genomics track overview
William Hersh, Aaron Cohen, Lynn Ruslen, and Phoebe Roberts. 2007 · 2007
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Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?
Hiroaki Sakamoto, Yasunori Watanabe, and Masataka Satou. 2011 · 2011
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Machine reading of biomedical texts about alzheimers disease
Roser Morante, Martin Krallinger, Alfonso Valencia, and Walter Daelemans. 2012 · 2012
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Qa4mre 2011-2013: Overview of question answering for machine reading evaluation
Anselmo Peñas, Eduard Hovy, Pamela Forner, Álvaro Rodrigo, Richard Sutcliffe, and Roser Morante. 2013 · 2013
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Distributional semantics resources for biomedical text processing
Sampo Pyysalo, Filip Ginter, Hans Moen, Tapio Salakoski, and Sophia Ananiadou. 2013 · 2013
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The Stanford CoreNLP natural language processing toolkit
Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014 · 2014
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An overview of the bioasq large-scale biomedical semantic indexing and question answering competition
George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, et al. 2015 · 2015
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Enhanced lstm for natural language inference
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Race: Large-scale reading comprehension dataset from examinations
Bag-of-words as target for neural machine translation
Shuming Ma, Xu Sun, Yizhong Wang, and Junyang Lin. 2018 · 2018
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emrqa: A large corpus for question answering on electronic medical records
Anusri Pampari, Preethi Raghavan, Jennifer Liang, and Jian Peng. 2018 · 2018
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Bioread: A new dataset for biomedical reading comprehension
Dimitris Pappas, Ion Androutsopoulos, and Haris Papageorgiou. 2018 · 2018
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Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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Interpretation of natural language rules in conversational machine reading
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Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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A pilot study of biomedical text comprehension using an attention-based deep neural reader: Design and experimental analysis
Seongsoon Kim, Donghyeon Park, Yonghwa Choi, Kyubum Lee, Byounggun Kim, Minji Jeon, Jihye Kim, Aik Choon Tan, and Jaewoo Kang. 2018 · 2018
Cited alongside, same era.
The narrativeqa reading comprehension challenge
Tomáš Kočiskỳ, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gáabor Melis, and Edward Grefenstette. 2018 · 2018
Cited alongside, same era.
Marzieh Saeidi, Max Bartolo, Patrick Lewis, Sameer Singh, Tim Rocktäschel, Mike Sheldon, Guillaume Bouchard, and Sebastian Riedel. 2018 · 2018
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
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Boolq: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019 · 2019
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Rhinehart, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, et al. 2019 · 2019
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