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Most work on neural natural language generation (NNLG) focus on controlling the content of the generated text.
A computational theory of prose style for natural language generation
David D McDonald and James D Pustejovsky. 1985 · 1985
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Generating natural language under pragmatic constraints
Eduard Hovy. 1987 · 1987
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Phrasing a text in terms the user can understand
John A Bateman and Cecile Paris. 1989 · 1989
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A new algorithm for data compression
Philip Gage. 1994 · 1994
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Linguistic style matching in social interaction
Kate G Niederhoffer and James W Pennebaker. 2002 · 2002
Earlier work this paper cites.
Generating texts with style
Richard Power, Donia Scott, and Nadjet Bouayad-Agha. 2003 · 2003
Earlier work this paper cites.
Sequence-to-sequence generation for spoken dialogue via deep syntax trees and strings
Ondřej Dušek and Filip Jurcicek. 2016b · 2008
Earlier work this paper cites.
Register, genre, and style
Douglas Biber and Susan Conrad. 2009 · 2009
Earlier work this paper cites.
Recurrent neural network based language model
Tomas Mikolov, Martin Karafiát, Lukas Burget, Jan Cernockỳ, and Sanjeev Khudanpur. 2010 · 2010
Earlier work this paper cites.
Generating texts in different styles
Ehud Reiter and Sandra Williams. 2010 · 2010
Cited alongside, same era.
Generation of formal and informal sentences
Fadi Abu Sheikha and Diana Inkpen. 2011 · 2011
Cited alongside, same era.
Controlling user perceptions of linguistic style: Trainable generation of personality traits
François Mairesse and Marilyn A Walker. 2011 · 2011
Cited alongside, same era.
Paraphrasing for style
Wei Xu, Alan Ritter, Bill Dolan, Ralph Grishman, and Colin Cherry. 2012 · 2012
Cited alongside, same era.
Detecting information-dense texts in multiple news domains
Yinfei Yang and Ani Nenkova. 2014 · 2014
Cited alongside, same era.
Capturing meaning in product reviews with character-level generative text models
Zachary C Lipton, Sharad Vikram, and Julian McAuley. 2015 · 2015
Globally coherent text generation with neural checklist models
Chloé Kiddon, Luke Zettlemoyer, and Yejin Choi. 2016 · 2016
Later among the works it cites.
Controlling output length in neural encoder-decoders
Yuta Kikuchi, Graham Neubig, Ryohei Sasano, Hiroya Takamura, and Manabu Okumura. 2016 · 2016
Later among the works it cites.
Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
Later among the works it cites.
A persona-based neural conversation model
Jiwei Li, Michel Galley, Chris Brockett, Georgios Spithourakis, Jianfeng Gao, and Bill Dolan. 2016 · 2016
Later among the works it cites.
What to talk about and how? selective generation using lstms with coarse-to-fine alignment
Hongyuan Mei, Mohit Bansal, and Matthew R. Walter. 2016 · 2016
Later among the works it cites.
An empirical analysis of formality in online communication
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Cited alongside, same era.
Inducing lexical style properties for paraphrase and genre differentiation
Ellie Pavlick and Ani Nenkova. 2015 · 2015
Cited alongside, same era.
Semantically conditioned lstm-based natural language generation for spoken dialogue systems
Tsung-Hsien Wen, Milica Gasic, Nikola Mrkšić, Pei-Hao Su, David Vandyke, and Steve Young. 2015 · 2015
Cited alongside, same era.
Incorporating side information into recurrent neural network language models
Cong Duy Vu Hoang, Gholamreza Haffari, and Trevor Cohn. 2016 · 2016
Cited alongside, same era.
A context-aware natural language generator for dialogue systems
Ondřej Dušek and Filip Jurcicek. 2016a
Cited in the paper.
Controlling politeness in neural machine translation via side constraints
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016a
Cited in the paper.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016b
Cited in the paper.
Ellie Pavlick and Joel Tetreault. 2016 · 2016
Later among the works it cites.
Context-aware natural language generation with recurrent neural networks
Jian Tang, Yifan Yang, Sam Carton, Ming Zhang, and Qiaozhu Mei. 2016 · 2016
Later among the works it cites.
Controllable text generation
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
Closest in time.
Learning to generate reviews and discovering sentiment
Alec Radford, Rafal Jozefowicz, and Ilya Sutskever. 2017 · 2017
Closest in time.