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Recurrent Neural Networks are showing much promise in many sub-areas of natural language processing, ranging from document classification to machine translation to automatic question answering.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
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Multiple object recognition with visual attention
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Alex Graves, Greg Wayne, and Ivo Danihelka. 2014 · 2014
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Adam: A method for stochastic optimization
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A clockwork rnn
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Distributed representations of sentences and documents
Quoc V. Le and Tomas Mikolov. 2014 · 2014
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Recurrent models of visual attention
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Attention for fine-grained categorization
Pierre Sermanet, Andrea Frome, and Esteban Real. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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William Chan, Navdeep Jaitly, Quoc V Le, and Oriol Vinyals. 2015 · 2015
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Semi-supervised sequence learning
Andrew M. Dai and Quoc V. Le. 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
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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Hierarchical multiscale recurrent neural networks
Junyoung Chung, Sungjin Ahn, and Yoshua Bengio. 2016 · 2016
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Adaptive computation time for recurrent neural networks
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Modeling human reading with neural attention
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2015 · 2015
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A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Neural responding machine for short-text conversation
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A neural network approach to context-sensitive generation of conversational responses
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Variable computation in recurrent neural networks
Yacine Jernite, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2016 · 2016
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Learning recurrent span representations for extractive question answering
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Rationalizing neural predictions
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Abstractive text summarization using sequence-to-sequence RNNs and beyond
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Bidirectional attention flow for machine comprehension
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Reasonet: Learning to stop reading in machine comprehension
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A parallel-hierarchical model for machine comprehension on sparse data
Adam Trischler, Zheng Ye, Xingdi Yuan, Jing He, Phillip Bachman, and Kaheer Suleman. 2016 · 2016
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Machine comprehension using match-lstm and answer pointer
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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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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 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 symbolic machines: Learning semantic parsers on freebase with weak supervision
Chen Liang, Jonathan Berant, Quoc Le, Kenneth D. Forbus, and Ni Lao. 2017 · 2017
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