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In this paper, drawing intuition from the Turing test, we propose using adversarial training for open-domain dialogue generation: the system is trained to produce sequences that are indistinguishable from human-generated dialogue utterances.
Computing machinery and intelligence
Alan M Turing. 1950 · 1950
Earlier work this paper cites.
Stochastic optimization
V. M. Aleksandrov, V. I. Sysoyev, and V. V. Shemeneva. 1968 · 1968
Earlier work this paper cites.
Likelihood ratio gradient estimation for stochastic systems
Peter W Glynn. 1990 · 1990
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams. 1992 · 1992
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Learning to classify text using support vector machines: Methods, theory and algorithms
Thorsten Joachims. 2002 · 2002
Earlier work this paper cites.
Data-driven response generation in social media
Alan Ritter, Colin Cherry, and William B Dolan. 2011 · 2011
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Earlier work this paper cites.
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Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Earlier work this paper cites.
Deep generative image models using a? laplacian pyramid of adversarial networks
Emily L Denton, Soumith Chintala, Rob Fergus, et al. 2015 · 2015
Earlier work this paper cites.
A hierarchical neural autoencoder for paragraphs and documents
Jiwei Li, Minh-Thang Luong, and Dan Jurafsky. 2015 · 2015
Earlier work this paper cites.
Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D Manning. 2015 · 2015
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
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David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al. 2016 · 2016
Later among the works it cites.
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Pei-Hao Su, Milica Gasic, Nikola Mrksic, Lina Rojas-Barahona, Stefan Ultes, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
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A network-based end-to-end trainable task-oriented dialogue system
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