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Machine reading comprehension with unanswerable questions is a challenging task.
Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019 · 1905
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Binary codes capable of correcting deletions, insertions, and reversals
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Long short-term memory
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Good Question! Statistical ranking for question generation
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Question answering using enhanced lexical semantic models
Wen-tau Yih, Ming-Wei Chang, Christopher Meek, and Andrzej Pastusiak. 2013 · 2013
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
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Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
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Ground truth for grammatical error correction metrics
Courtney Napoles, Keisuke Sakaguchi, Matt Post, and Joel Tetreault. 2015 · 2015
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Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O.K. Li. 2016 · 2016
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MS MARCO: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 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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Learning to ask: Neural question generation for reading comprehension
Xinya Du, Junru Shao, and Claire Cardie. 2017 · 2017
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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OpenNMT: Open-source toolkit for neural machine translation
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander Rush. 2017 · 2017
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FusionNet: Fusing via fully-aware attention with application to machine comprehension
Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, and Weizhu Chen. 2018 · 2018
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The NarrativeQA reading comprehension challenge
Tomas Kocisky, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gabor Melis, and Edward Grefenstette. 2018 · 2018
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Stochastic answer networks for machine reading comprehension
Xiaodong Liu, Yelong Shen, Kevin Duh, and Jianfeng Gao. 2018 · 2018
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Know what you don’t know: Unanswerable questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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Linfeng Song, Zhiguo Wang, Wael Hamza, Yue Zhang, and Daniel Gildea. 2018 · 2018
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Answer-focused and position-aware neural question generation
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Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
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Machine comprehension using Match-LSTM and answer pointer
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Dynamic coattention networks for question answering
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I know there is no answer: Modeling answer validation for machine reading comprehension
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Multi-granularity hierarchical attention fusion networks for reading comprehension and question answering
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Fast and accurate reading comprehension by combining self-attention and convolution
Adams Wei Yu, David Dohan, Quoc Le, Thang Luong, Rui Zhao, and Kai Chen. 2018 · 2018
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Neural question generation from text: A preliminary study
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