Fetching the paper…
Reading the bibliography…
Neural networks are very powerful learning systems, but they do not readily generalize from one task to the other.
Universal Grammar
Montague, Richard · 1970
Earlier work this paper cites.
The Society of Mind
Minsky, Marvin · 1986
Earlier work this paper cites.
Connectionism and cognitive architecture: A critical analysis
Fodor, Jerry and Pylyshyn, Zenon · 1988
Earlier work this paper cites.
Finding structure in time
Elman, Jeffrey · 1990
Earlier work this paper cites.
Towards compositional learning in dynamic networks
Schmidhuber, Jürgen · 1990
Earlier work this paper cites.
Learning and extracting finite state automata with second-order recurrent neural networks
Giles, C Lee, Miller, Clifford B, Chen, Dong, Chen, Hsing-Hen, Sun, Guo-Zheng, and Lee, Yee-Chun · 1992
Earlier work this paper cites.
Transfer of learning by composing solutions of elemental sequential tasks
Singh, Satinder · 1992
Earlier work this paper cites.
Long short-term memory
Hochreiter, Sepp and Schmidhuber, Jürgen · 1997
Earlier work this paper cites.
Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
Sutton, Richard, Precup, Doina, and Singh, Satinder · 1999
Earlier work this paper cites.
The Compositionality Papers
Fodor, Jerry and Lepore, Ernest · 2002
Earlier work this paper cites.
The faculty of language: What is it, who has it, and how did it evolve?
Hauser, Marco, Chomsky, Noam, and Fitch, Tecumseh · 2002
Cited alongside, same era.
Evolving neural networks through augmenting topologies
Stanley, Kenneth and Miikkulainen, Risto · 2002
Cited alongside, same era.
Recent advances in hierarchical reinforcement learning
Barto, Andrew and Mahadevan, Sridhar · 2003
Cited alongside, same era.
Transfer learning for reinforcement learning domains: A survey
Taylor, Matthew and Stone, Peter · 2009
Cited alongside, same era.
Recurrent neural network based language model
Mikolov, Tomas, Karafiát, Martin, Burget, Lukás, Cernocký, Jan, and Khudanpur, Sanjeev · 2010
Cited alongside, same era.
Adam: A method for stochastic optimization
Kingma, Diederik P and Ba, Jimmy · 2014
Probing the compositionality of intuitive functions
Schulz, Eric, Tenenbaum, Josh, Duvenaud, David, Speekenbrink, Maarten, and Gershman, Samuel · 2016
Later among the works it cites.
Modular multitask reinforcement learning with policy sketches
Andreas, Jacob, Klein, Dan, and Levine, Sergey · 2017
Later among the works it cites.
Learning to reason: End-to-end module networks for visual question answering
Hu, Ronghang, Andreas, Jacob, Rohrbach, Marcus, Darrell, Trevor, and Saenko, Kate · 2017
Later among the works it cites.
CLEVR: a diagnostic dataset for compositional language and elementary visual reasoning
Johnson, Justin, Hariharan, Bharath, van der Maaten, Laurens, Fei-Fei, Li, Zitnick, Lawrence, and Girshick, Ross · 2017
Later among the works it cites.
Lake, Brenden and Baroni, Marco · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Sequence to sequence learning with neural networks
Sutskever, Ilya, Vinyals, Oriol, and Le, Quoc · 2014
Cited alongside, same era.
Deep learning
LeCun, Yann, Bengio, Yoshua, and Hinton, Geoffrey · 2015
Cited alongside, same era.
Learning to compose neural networks for question answering
Andreas, Jacob, Rohrbach, Marcus, Darrell, Trevor, and Klein, Dan · 2016
Cited alongside, same era.
Compositional reasoning in early childhood
Piantadosi, Steven and Aslin, Richard · 2016
Cited alongside, same era.
Building machines that learn and think like people
Lake, Brenden, Ullman, Tomer, Tenenbaum, Joshua, and Gershman, Samuel · 2017
Later among the works it cites.
Sahni, Himanshu, Tejani, Farhan, Kumar, Saurabh, and Isbell, Charles · 2017
Later among the works it cites.
Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks
Soltoggio, Andrea, Stanley, Kenneth, and Risi, Sebastian · 2017
Later among the works it cites.
Extracting automata from recurrent neural networks using queries and counterexamples
Weiss, Gail, Goldberg, Yoav, and Yahav, Eran · 2017
Later among the works it cites.