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Open domain Question Answering (QA) systems must interact with external knowledge sources, such as web pages, to find relevant information.
Building a question answering test collection
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Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
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Semantic parsing on freebase from question-answer pairs
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Learning phrase representations using rnn encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
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Open question answering over curated and extracted knowledge bases
Anthony Fader, Luke Zettlemoyer, and Oren Etzioni. 2014 · 2014
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Wikidata: a free collaborative knowledgebase
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Knowledge base completion via search-based question answering
Robert West, Evgeniy Gabrilovich, Kevin Murphy, Shaohua Sun, Rahul Gupta, and Dekang Lin. 2014 · 2014
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Clustering is efficient for approximate maximum inner product searrch
Alex Auvolat, Sarath Chandar, Pascal Vincent, Hugo Larochelle, and Yoshua Bengio. 2015 · 2015
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Neural machine translation by jointly learning to align and translate
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Large-scale simple question answering with memory networks
Antoine Bordes, Nicolas Usunier, Sumit Chopra, and Jason Weston. 2015 · 2015
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba. 2015 · 2015
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A neural knowledge language model
Sungjin Ahn, Heeyoul Choi, Tanel Pärnamaa, and Yoshua Bengio. 2016 · 2016
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Gated-attention readers for text comprehension
Bhuwan Dhingra, Hanxiao Liu, William Cohen, and Ruslan Salakhutdinov. 2016 · 2016
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Text understanding with the attention sum reader network
Rudolf Kadlec, Martin Schmid, Ondřej Bajgar, and Jan Kleindienst. 2016 · 2016
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Pointer sentinel mixture models
Stephen Merity, Xiong Caiming, Bradbury James, and Richard Socher. 2016 · 2016
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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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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Emergent logical structure in vector representations of neural readers
Hai Wang, Takeshi Onishi, Kevin Gimpel, and David McAllester. 2016 · 2016
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Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, and Yoshua Bengio. 2016 · 2016
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A thorough examination of the cnn/daily mail reading comprehension task
Danqi Chen, Jason Bolton, and Christopher D. Manning. 2016 · 2016
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Hierarchical question answering for long documents
Eunsol Choi, Daniel Hewlett, Alexandre Lacoste, Illia Polosukhin, Jakob Uszkoreit, and Jonathan Berant. 2016 · 2016
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Dynamic coattention networks for question answering
Caiming Xiong, Victor Zhong, and Richard Socher. 2016 · 2016
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V. Le. 2016 · 2016
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