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Ubuntu dialogue corpus is the largest public available dialogue corpus to make it feasible to build end-to-end deep neural network models directly from the conversation data.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Modern information retrieval , volume 463
Ricardo Baeza-Yates, Berthier Ribeiro-Neto, et al · 1999
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The trec-8 question answering track report
Ellen M Voorhees et al · 1999
Earlier work this paper cites.
Data-driven response generation in social media
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Earlier work this paper cites.
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Adam: A method for stochastic optimization
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Earlier work this paper cites.
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Earlier work this paper cites.
Glove: Global vectors for word representation
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Earlier work this paper cites.
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Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, and Grégoire Mesnil · 2014
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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 Miller, Arthur Szlam, and Jason Weston · 2015
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Improved deep learning baselines for ubuntu corpus dialogs
Rudolf Kadlec, Martin Schmid, and Jan Kleindienst · 2015
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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 · 2015
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Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi · 2016
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Robert Speer and Joshua Chin · 2016
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Training end-to-end dialogue systems with the ubuntu dialogue corpus
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Conceptnet 5.5: An open multilingual graph of general knowledge
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