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Even though machine learning has become the major scene in dialogue research community, the real breakthrough has been blocked by the scale of data available.
A proposal for the dartmouth summer research project on artificial intelligence
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Deep neural network approach for the dialog state tracking challenge
Matthew Henderson, Blaise Thomson, and Steve Young. 2013 · 2013
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The dialog state tracking challenge
Jason Williams, Antoine Raux, Deepak Ramachandran, and Alan Black. 2013 · 2013
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POMDP-based Statistical Spoken Dialogue Systems: a Review
Steve Young, Milica Gašić, Blaise Thomson, and Jason Williams. 2013 · 2013
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Incremental on-line adaptation of pomdp-based dialogue managers to extended domains
A diversity-promoting objective function for neural conversation models
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How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
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Towards end-to-end learning for dialog state tracking and management using deep reinforcement learning
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Frames: A corpus for adding memory to goal-oriented dialogue systems
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Milica Gašić, Dongho Kim, Pirros Tsiakoulis, Catherine Breslin, Matthew Henderson, Martin Szummer, Blaise Thomson, and Steve Young. 2014 · 2014
Cited alongside, same era.
Gaussian processes for pomdp-based dialogue manager optimization
Milica Gašić and Steve Young. 2014 · 2014
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The third dialog state tracking challenge
Matthew Henderson, Blaise Thomson, and Jason D Williams. 2014c · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Cited alongside, same era.
The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems
Ryan Lowe, Nissan Pow, Iulian V Serban, and Joelle Pineau. 2015 · 2015
Cited alongside, same era.
Using recurrent neural networks for slot filling in spoken language understanding
Grégoire Mesnil, Yann Dauphin, Kaisheng Yao, Yoshua Bengio, Li Deng, Dilek Hakkani-Tur, Xiaodong He, Larry Heck, Gokhan Tur, Dong Yu, et al. 2015 · 2015
Cited alongside, same era.
An analysis of domestic abuse discourse on reddit
Nicolas Schrading, Cecilia Ovesdotter Alm, Ray Ptucha, and Christopher Homan. 2015 · 2015
Cited alongside, same era.
Learning end-to-end goal-oriented dialog
Antoine Bordes, Y-Lan Boureau, and Jason Weston. 2017 · 2017
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Key-value retrieval networks for task-oriented dialogue
Mihail Eric, Lakshmi Krishnan, Francois Charette, and Christopher D Manning. 2017 · 2017
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The fourth dialog state tracking challenge
Seokhwan Kim, Luis Fernando D’Haro, Rafael E Banchs, Jason D Williams, and Matthew Henderson. 2017 · 2017
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End-to-end task-completion neural dialogue systems
Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao, and Asli Celikyilmaz. 2017 · 2017
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Scalable multi-domain dialogue state tracking
Abhinav Rastogi, Dilek Hakkani-Tur, and Larry Heck. 2017 · 2017
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A network-based end-to-end trainable task-oriented dialogue system
Tsung-Hsien Wen, David Vandyke, Nikola Mrksic, Milica Gašić, Lina M Rojas-Barahona, Pei-Hao Su, Stefan Ultes, and Steve Young. 2017 · 2017
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Towards end-to-end multi-domain dialogue modelling
Paweł Budzianowski, Iñigo Casanueva, Bo-Hsiang Tseng, and Milica Gašić. 2018 · 2018
Closest in time.
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, et al. 2018 · 2018
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Large-scale multi-domain belief tracking with knowledge sharing
Osman Ramadan, Paweł Budzianowski, and Milica Gašić. 2018 · 2018
Closest in time.
Building a conversational agent overnight with dialogue self-play
P Shah, D Hakkani-Tur, G Tur, A Rastogi, A Bapna, N Nayak, and L Heck. 2018 · 2018
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Benchmarking uncertainty estimates with deep reinforcement learning for dialogue policy optimisation
Christopher Tegho, Paweł Budzianowski, and Milica Gašić. 2018 · 2018
Closest in time.