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Creating an intelligent conversational system that understands vision and language is one of the ultimate goals in Artificial Intelligence (AI)~\cite{winograd1972understanding}.
Understanding natural language
Terry Winograd. 1972 · 1972
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Feudal reinforcement learning
Peter Dayan and Geoffrey E Hinton. 1993 · 1993
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Policy invariance under reward transformations: Theory and application to reward shaping
Andrew Y Ng, Daishi Harada, and Stuart Russell. 1999 · 1999
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Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning
Richard S Sutton, Doina Precup, and Satinder Singh. 1999 · 1999
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Hierarchical reinforcement learning with the maxq value function decomposition
Thomas G Dietterich. 2000 · 2000
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Optimizing dialogue management with reinforcement learning: Experiments with the njfun system
Satinder Singh, Diane Litman, Michael Kearns, and Marilyn Walker. 2002 · 2002
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Hierarchical reinforcement learning of dialogue policies in a development environment for dialogue systems: Reall-dude
Oliver Lemon, Xingkun Liu, Daniel Shapiro, and Carl Tollander. 2006 · 2006
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Partially observable markov decision processes for spoken dialog systems
Jason D Williams and Steve Young. 2007 · 2007
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Evaluation of a hierarchical reinforcement learning spoken dialogue system
Heriberto Cuayáhuitl, Steve Renals, Oliver Lemon, and Hiroshi Shimodaira. 2010 · 2010
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Reinforcement learning of argumentation dialogue policies in negotiation
Kallirroi Georgila and David Traum. 2011 · 2011
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Pomdp-based let’s go system for spoken dialog challenge
Sungjin Lee and Maxine Eskenazi. 2012 · 2012
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Unifying visual-semantic embeddings with multimodal neural language models
Ryan Kiros, Ruslan Salakhutdinov, and Richard S Zemel. 2014 · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick. 2015 · 2015
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Deep reinforcement learning with a natural language action space
Sub-domain modelling for dialogue management with hierarchical reinforcement learning
Pawel Budzianowski, Stefan Ultes, Pei-Hao Su, Nikola Mrksic, Tsung-Hsien Wen, Inigo Casanueva, Lina Rojas-Barahona, and Milica Gasic. 2017 · 2017
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Evaluating visual conversational agents via cooperative human-ai games
Prithvijit Chattopadhyay, Deshraj Yadav, Viraj Prabhu, Arjun Chandrasekaran, Abhishek Das, Stefan Lee, Dhruv Batra, and Devi Parikh. 2017 · 2017
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Guesswhat?! visual object discovery through multi-modal dialogue
Harm De Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, and Aaron Courville. 2017 · 2017
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Best of both worlds: Transferring knowledge from discriminative learning to a generative visual dialog model
Jiasen Lu, Anitha Kannan, Jianwei Yang, Devi Parikh, and Dhruv Batra. 2017 · 2017
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Using reinforcement learning to model incrementality in a fast-paced dialogue game
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Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, and Mari Ostendorf. 2015 · 2015
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Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei. 2015 · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al. 2015 · 2015
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Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver. 2015 · 2015
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Natural language object retrieval
Ronghang Hu, Huazhe Xu, Marcus Rohrbach, Jiashi Feng, Kate Saenko, and Trevor Darrell. 2016 · 2016
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Generating natural questions about an image
Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, Margaret Mitchell, Xiaodong He, and Lucy Vanderwende. 2016 · 2016
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Tiancheng Zhao and Maxine Eskenazi. 2016 · 2016
Cited alongside, same era.
Visual dialog
Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José MF Moura, Devi Parikh, and Dhruv Batra. 2017a
Cited in the paper.
Ramesh Manuvinakurike, David DeVault, and Kallirroi Georgila. 2017 · 2017
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Image-grounded conversations: Multimodal context for natural question and response generation
Nasrin Mostafazadeh, Chris Brockett, Bill Dolan, Michel Galley, Jianfeng Gao, Georgios P Spithourakis, and Lucy Vanderwende. 2017 · 2017
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How to make context more useful? an empirical study on context-aware neural conversational models
Zhiliang Tian, Rui Yan, Lili Mou, Yiping Song, Yansong Feng, and Dongyan Zhao. 2017 · 2017
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Learning conversational systems that interleave task and non-task content
Zhou Yu, Alan W Black, and Alexander I Rudnicky. 2017 · 2017
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Asking the difficult questions: Goal-oriented visual question generation via intermediate rewards
Junjie Zhang, Qi Wu, Chunhua Shen, Jian Zhang, Jianfeng Lu, and Anton van den Hengel. 2017 · 2017
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Feudal reinforcement learning for dialogue management in large domains
Iñigo Casanueva, Paweł Budzianowski, Pei-Hao Su, Stefan Ultes, Lina Rojas-Barahona, Bo-Hsiang Tseng, and Milica Gašić. 2018 · 2018
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Deep reinforcement learning with double q-learning
Hado Van Hasselt, Arthur Guez, and David Silver. 2016 · 2094
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