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We introduce a large scale MAchine Reading COmprehension dataset, which we name MS MARCO.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
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K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu · 2002
Earlier work this paper cites.
Challenges in adopting speech recognition
L. Deng and X. Huang · 2004
Earlier work this paper cites.
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
S. Banerjee and A. Lavie · 2005
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Imagenet: Alarge-scalehierarchicalimagedatabas
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fe · 2009
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
S. Robertson, H. Zaragoza, et al · 2009
Earlier work this paper cites.
Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition
G. Dahl, D. Yu, L. Deng, and A. Acero · 2012
Earlier work this paper cites.
Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
G. Hinton, L. Deng, D. Yu, G. Dalh, and A. Mohamed · 2012
Earlier work this paper cites.
Learning deep structured semantic models for web search using clickthrough data
P.-S. Huang, X. He, J. Gao, L. Deng, A. Acero, and L. Heck · 2013
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
D. Bahdanau, K. Cho, and Y. Bengio · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. V. Le · 2014
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Earlier work this paper cites.
End-to-end memory networks
S. Sukhbaatar, J. Weston, R. Fergus, et al · 2015
Earlier work this paper cites.
Towards ai-complete question answering: A set of prerequisite toy tasks
J. Weston, A. Bordes, S. Chopra, A. M. Rush, B. van Merrienboer, A. Joulin, and T. Mikolov · 2015
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Long short-term memory-networks for machine reading
J. Cheng, L. Dong, and M. Lapata · 2016
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Text understanding with the attention sum reader network
R. Kadlec, M. Schmid, O. Bajgar, and J. Kleindienst · 2016
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A proposal for evaluating answer distillation from web data
B. Mitra, G. Simon, J. Gao, N. Craswell, and L. J. Deng · 2016
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Squad: 100,000+ questions for machine comprehension of text
P. Rajpurkar, J. Zhang, K. Lopyrev, and P. Liang · 2016
The rouge-ar: A proposed extension to the rouge evaluation metric for abstractive text summarization
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Newsqa: A machine comprehension dataset
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Amazon Echo · 2018
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Think you have solved question answering? try arc, the ai2 reasoning challenge
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Reasonet: Learning to stop reading in machine comprehension
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Simple and effective multi-paragraph reading comprehension
C. Clark and M. Gardner · 2017
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M. Dunn, L. Sagun, M. Higgins, V. U. Güney, V. Cirik, and K. Cho · 2017
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Google brain chief: Deep learning takes at least 100,000 examples
B. H. Frank · 2017
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Dureader: a chinese machine reading comprehension dataset from real-world applications
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