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We study the task of generating from Wikipedia articles question-answer pairs that cover content beyond a single sentence.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
Understanding natural language
Terry Winograd. 1972 · 1972
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
John Lafferty, Andrew McCallum, and Fernando CN Pereira. 2001 · 2001
Earlier work this paper cites.
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Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Computer-aided generation of multiple-choice tests
Ruslan Mitkov and Le An Ha. 2003 · 2003
Earlier work this paper cites.
Good question! statistical ranking for question generation
Michael Heilman and Noah A. Smith. 2010 · 2010
Earlier work this paper cites.
Syntactic and semantic structure for opinion expression detection
Richard Johansson and Alessandro Moschitti. 2010 · 2010
Earlier work this paper cites.
The first question generation shared task evaluation challenge
Vasile Rus, Brendan Wyse, Paul Piwek, Mihai Lintean, Svetlana Stoyanchev, and Cristian Moldovan. 2010 · 2010
Earlier work this paper cites.
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Hector J Levesque, Ernest Davis, and Leora Morgenstern. 2011 · 2011
Earlier work this paper cites.
Question generation from concept maps
Andrew M Olney, Arthur C Graesser, and Natalie K Person. 2012 · 2012
Earlier work this paper cites.
Semantics-based question generation and implementation
Xuchen Yao, Gosse Bouma, and Yi Zhang. 2012 · 2012
Earlier work this paper cites.
Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013 · 2013
Earlier work this paper cites.
On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. 2013 · 2013
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Meteor universal: Language specific translation evaluation for any target language
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Ozan Irsoy and Claire Cardie. 2014 · 2014
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Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Antoine Bordes, Nicolas Usunier, Sumit Chopra, and Jason Weston. 2015 · 2015
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Key-value memory networks for directly reading documents
Alexander Miller, Adam Fisch, Jesse Dodge, Amir-Hossein Karimi, Antoine Bordes, and Jason Weston. 2016 · 2016
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Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Generating factoid questions with recurrent neural networks: The 30m factoid question-answer corpus
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Multi-perspective context matching for machine comprehension
Zhiguo Wang, Haitao Mi, Wael Hamza, and Radu Florian. 2016 · 2016
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Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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Bidirectional lstm-crf models for sequence tagging
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Deep questions without deep understanding
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Improving coreference resolution by learning entity-level distributed representations
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Language modeling with gated convolutional networks
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Learning to ask: Neural question generation for reading comprehension
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Question generation for question answering
Nan Duan, Duyu Tang, Peng Chen, and Ming Zhou. 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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Generating natural language question-answer pairs from a knowledge graph using a rnn based question generation model
Sathish Reddy, Dinesh Raghu, Mitesh M. Khapra, and Sachindra Joshi. 2017 · 2017
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Neural question generation from text: A preliminary study
Qingyu Zhou, Nan Yang, Furu Wei, Chuanqi Tan, Hangbo Bao, and Ming Zhou. 2017 · 2017
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R3: Reinforced ranker-reader for open-domain question answering
Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerald Tesauro, Bowen Zhou, and Jing Jiang. 2018 · 2018
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Identifying where to focus in reading comprehension for neural question generation
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