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To solve the text-based question and answering task that requires relational reasoning, it is necessary to memorize a large amount of information and find out the question relevant information from the memory.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
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Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Memory networks
S. Chopra J. Weston and A. Bordes · 2015
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End-to-end memory networks
Sainbayar Sukhbaatar, Jason Weston, Rob Fergus, et al · 2015
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Towards ai-complete question answering: A set of prerequisite toy tasks
Jason Weston, Antoine Bordes, Sumit Chopra, and Tomas Mikolov · 2015
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Learning end-to-end goal-oriented dialog
Antoine Bordes and Jason Weston · 2016
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Ask me anything: Dynamic memory networks for natural language processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, and Richard Socher · 2016
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Dynamic memory networks for visual and textual question answering
Caiming Xiong, Stephen Merity, and Richard Socher · 2016
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Gated end-to-end memory networks
Fei Liu and Julien Perez · 2017
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A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David GT Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap · 2017
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