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We present deep communicating agents in an encoder-decoder architecture to address the challenges of representing a long document for abstractive summarization.
New york times annotated corpus
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Kai Hong and Ani Nenkova. 2014 · 2014
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Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014 · 2014
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Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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System combination for multi-document summarization
Kai Hong, Michel Marcus, and Ani Nenkova. 2015 · 2015
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Minh-Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Neural sentiment classification with user and product attention
Huimin Chen, Maosong Sun, Cunchao Tu, Yankai Lin, and Zhiyuan Liu. 2016 · 2016
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Neural summarization by extracting sentences and words
Jianpeng Cheng and Mirella Lapata. 2016 · 2016
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Abstractive sentence summarization with attentive recurrent neural networks
Sumit Chopra, Michael Auli, and Alexander M. Rush. 2016 · 2016
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Learning-based single-document summarization with compression and anaphoricity constraints
Greg Durrett, Taylor Berg-Kirkpatrick, and Dan Klein. 2016 · 2016
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Learning to communicate with deep multi-agent reinforcement learning
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, and Shimon Whiteson. 2016 · 2016
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Towards multi-agent communication-based language learning
Angeliki Lazaridou, Nghia The Pham, and Marco Baroni. 2016 · 2016
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The role of discourse units in near-extractive summarization
Junyi Jessy Li, Kapil Thandani, and Amanda Stent. 2016 · 2016
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Learning cooperative visual dialog agents with deep reinforcement learning
Abhishek Das, Satwik Kottur, José M. F. Moura, and Dhruv Batra Stefan Lee. 2017 · 2017
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Controllable abstractive summarization
Angela Fan, David Grangier, and Michael Auli. 2017 · 2017
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Counterfactual multi-agent policy gradients
J. Foerster, G. Farquhar, T. Afouras, N. Nardelli, and S. Whiteson. 2017 · 2017
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Sequence tutor: Conservative fine-tuning of sequence generation models with kl-control
Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, Jose Miguel Hernandez-Lobato, Richard E. Turner, and Douglas Eck. 2017 · 2017
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Emergence of grounded compositional language in multi-agent populations
I. Mordatch and P. Abbeel. 2017 · 2017
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Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015a
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Gettothepoint: Summarization with pointer-generatornetworks
Abigale See, Peter J. Liu, and Christopher Manning. 2017 · 2017
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Abstractive document summarization with a graph-based attentional neural model
Jiwei Tan, Xiaojun Wan, and Jianguo Xiao. 2017 · 2017
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Starcraft ii: A new challenge for reinforcement learning
O. Vinyals, T. Ewalds, S. Bartunov, P. Georgiev, A. S. Vezhnevets, M. Yeo, A. Makhzani, H. Kuttler, J. Agapiou, and J. et al. Schrittwieser. 2017 · 2017
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A deep reinforced model for abstractive summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 2018 · 2018
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