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Existing dialog datasets contain a sequence of utterances and responses without any explicit background knowledge associated with them.
Dropout: a simple way to prevent neural networks from overfitting
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Development and preliminary evaluation of the MIT ATIS system
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Schema theory
Diane L. Schallert. 2002 · 2002
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Answering the call for a standard reliability measure for coding data
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Adaptive subgradient methods for online learning and stochastic optimization
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ADADELTA: an adaptive learning rate method
Matthew D. Zeiler. 2012 · 2012
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The dialog state tracking challenge
Jason D. Williams, Antoine Raux, Deepak Ramachandran, and Alan W. Black. 2013 · 2013
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The second dialog state tracking challenge
Matthew Henderson, Blaise Thomson, and Jason D. Williams. 2014a · 2014
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The third dialog state tracking challenge
Matthew Henderson, Blaise Thomson, and Jason D. Williams. 2014b · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning. 2014 · 2014
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The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems
Ryan Lowe, Nissan Pow, Iulian Serban, and Joelle Pineau. 2015b · 2015
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A survey of available corpora for building data-driven dialogue systems
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, and Joelle Pineau. 2015 · 2015
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Neural responding machine for short-text conversation
Lifeng Shang, Zhengdong Lu, and Hang Li. 2015 · 2015
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A neural network approach to context-sensitive generation of conversational responses
Alessandro Sordoni, Michel Galley, Michael Auli, Chris Brockett, Yangfeng Ji, Margaret Mitchell, Jian-Yun Nie, Jianfeng Gao, and Bill Dolan. 2015 · 2015
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A knowledge-grounded neural conversation model
Marjan Ghazvininejad, Chris Brockett, Ming-Wei Chang, Bill Dolan, Jianfeng Gao, Wen-tau Yih, and Michel Galley. 2017 · 2017
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Eigen: A step towards conversational ai
William H. Guss, James Bartlett, Phillip Kuznetsov, and Piyush Patil. 2017 · 2017
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Learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings
He He, Anusha Balakrishnan, Mihail Eric, and Percy Liang. 2017 · 2017
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Edina: Building an open domain socialbot with self-dialogues
Ben Krause, Marco Damonte, Mihai Dobre, Daniel Duma, Joachim Fainberg, Federico Fancellu, Emmanuel Kahembwe, Jianpeng Cheng, and Bonnie L. Webber. 2017 · 2017
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Deal or no deal? end-to-end learning of negotiation dialogues
Mike Lewis, Denis Yarats, Yann Dauphin, Devi Parikh, and Dhruv Batra. 2017 · 2017
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A neural conversational model
Oriol Vinyals and Quoc V. Le. 2015 · 2015
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Evaluating prerequisite qualities for learning end-to-end dialog systems
Jesse Dodge, Andreea Gane, Xiang Zhang, Antoine Bordes, Sumit Chopra, Alexander H. Miller, Arthur Szlam, and Jason Weston. 2016 · 2016
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A persona-based neural conversation model
Jiwei Li, Michel Galley, Chris Brockett, Georgios P. Spithourakis, Jianfeng Gao, and William B. Dolan. 2016 · 2016
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Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, and Joelle Pineau. 2016 · 2016
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The dialog state tracking challenge series: A review
Jason D. Williams, Antoine Raux, and Matthew Henderson. 2016 · 2016
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Learning end-to-end goal-oriented dialog
Antoine Bordes and Jason Weston. 2017 · 2017
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Conversational AI: the science behind the alexa prize
Ashwin Ram, Rohit Prasad, Chandra Khatri, Anu Venkatesh, Raefer Gabriel, Qing Liu, Jeff Nunn, Behnam Hedayatnia, Ming Cheng, Ashish Nagar, Eric King, Kate Bland, Amanda Wartick, Yi Pan, Han Song, Sk Jayadevan, Gene Hwang, and Art Pettigrue. 2017 · 2017
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A network-based end-to-end trainable task-oriented dialogue system
Lina Maria Rojas-Barahona, Milica Gasic, Nikola Mrksic, Pei-Hao Su, Stefan Ultes, Tsung-Hsien Wen, Steve J. Young, and David Vandyke. 2017 · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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Bidirectional attention flow for machine comprehension
Min Joon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
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A hierarchical latent variable encoder-decoder model for generating dialogues
Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, and Yoshua Bengio. 2017b · 2017
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Gated self-matching networks for reading comprehension and question answering
Wenhui Wang, Nan Yang, Furu Wei, Baobao Chang, and Ming Zhou. 2017 · 2017
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Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, NAACL-HTL 2018, New Orleans, Louisiana, USA, June 2-4, 2018, Demonstrations . Association for Computational Linguistics
Yang Liu, Tim Paek, and Manasi Patwardhan, editors. 2018 · 2018
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