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The uptake of deep learning in natural language generation (NLG) led to the release of both small and relatively large parallel corpora for training neural models.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Trainable sentence planning for complex information presentation in spoken dialog systems
Amanda Stent, Rashmi Prasad, and Marilyn Walker. 2004 · 2004
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Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments
Alon Lavie and Abhaya Agarwal. 2007 · 2007
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Training and evaluation of the HIS POMDP dialogue system in noise
Milica Gašić, Simon Keizer, Francois Mairesse, Jost Schatzmann, Blaise Thomson, Kai Yu, and Steve Young. 2008 · 2008
Earlier work this paper cites.
Phrase-based statistical language generation using graphical models and active learning
François Mairesse, Milica Gašić, Filip Jurčíček, Simon Keizer, Blaise Thomson, Kai Yu, and Steve Young. 2010 · 2010
Earlier work this paper cites.
Amazon’s mechanical turk: A new source of inexpensive, yet high-quality, data?
Michael Buhrmester, Tracy Kwang, and Samuel D Gosling. 2011 · 2011
Earlier work this paper cites.
Enhancing the expression of contrast in the SPaRKy restaurant corpus
David Howcroft, Crystal Nakatsu, and Michael White. 2013 · 2013
Earlier work this paper cites.
Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Cited alongside, same era.
Sequence-to-sequence generation for spoken dialogue via deep syntax trees and strings
Ondřej Dušek and Filip Jurčíček. 2016 · 2016
Cited alongside, same era.
Multi-domain neural network language generation for spoken dialogue systems
Tsung-Hsien Wen, Milica Gašić, Nikola Mrkšić, Lina M. Rojas-Barahona, Pei-Hao Su, David Vandyke, and Steve Young. 2016 · 2016
Cited alongside, same era.
Learning robust dialog policies in noisy environments
Maryam Fazel-Zarandi, Shang-Wen Li, Jin Cao, Jared Casale, Peter Henderson, David Whitney, and Alborz Geramifard. 2017 · 2017
Cited alongside, same era.
Creating training corpora for micro-planners
Claire Gardent, Anastasia Shimorina, Shashi Narayan, and Laura Perez-Beltrachini. 2017 · 2017
Cited alongside, same era.
End-to-end task-completion neural dialogue systems
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Syntactic manipulation for generating more diverse and interesting texts
Jan Milan Deriu and Mark Cieliebak. 2018 · 2018
Later among the works it cites.
A deep ensemble model with slot alignment for sequence-to-sequence natural language generation
Juraj Juraska, Panagiotis Karagiannis, Kevin Bowden, and Marilyn Walker. 2018 · 2018
Later among the works it cites.
Characterizing variation in crowd-sourced data for training neural language generators to produce stylistically varied outputs
Juraj Juraska and Marilyn Walker. 2018 · 2018
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Advancing the state of the art in open domain dialog systems through the alexa prize
Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh, Jeff Nunn, Yi Pan, Qing Liu, Han Song, Anna Gottardi, Sanjeev Kwatra, Sanju Pancholi, et al. 2018 · 2018
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Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao, and Asli Celikyilmaz. 2017 · 2017
Cited alongside, same era.
To plan or not to plan? discourse planning in slot-value informed sequence to sequence models for language generation
Neha Nayak, Dilek Hakkani-Tür, Marilyn Walker, and Larry Heck. 2017 · 2017
Cited alongside, same era.
The E2E NLG shared task
Jekaterina Novikova, Ondřej Dušek, and Verena Rieser. 2017 · 2017
Cited alongside, same era.
Stochastic language generation in dialogue using recurrent neural networks with convolutional sentence reranking
Tsung-Hsien Wen, Milica Gašić, Dongho Kim, Nikola Mrkšić, Pei hao Su, David Vandyke, and Steve Young. 2015a
Cited in the paper.
Semantically conditioned lstm-based natural language generation for spoken dialogue systems
Tsung-Hsien Wen, Milica Gašić, Nikola Mrkšić, Pei-Hao Su, David Vandyke, and Steve Young. 2015b
Cited in the paper.
Towards exploiting background knowledge for building conversation systems
Nikita Moghe, Siddhartha Arora, Suman Banerjee, and Mitesh M Khapra. 2018 · 2018
Later among the works it cites.
Building a conversational agent overnight with dialogue self-play
Pararth Shah, Dilek Hakkani-Tür, Gokhan Tür, Abhinav Rastogi, Ankur Bapna, Neha Nayak, and Larry Heck. 2018 · 2018
Later among the works it cites.
Evaluating the state-of-the-art of end-to-end natural language generation: The e2e nlg challenge
Ondřej Dušek, Jekaterina Novikova, and Verena Rieser. 2019 · 2019
Closest in time.