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Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph into a word sequence.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Ward Todd, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Statistical phrase-based translation
Philipp Koehn, Franz J. Och, and Daniel Marcu. 2003 · 2003
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Training tree transducers
Jonathan Graehl and Kevin Knight. 2004 · 2004
Earlier work this paper cites.
Statistical significance tests for machine translation evaluation
Philipp Koehn. 2004 · 2004
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
Earlier work this paper cites.
Hierarchical phrase-based translation
David Chiang. 2007 · 2007
Earlier work this paper cites.
Abstract meaning representation for sembanking
Laura Banarescu, Claire Bonial, Shu Cai, Madalina Georgescu, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Philipp Koehn, Martha Palmer, and Nathan Schneider. 2013 · 2013
Earlier work this paper cites.
Speech recognition with deep recurrent neural networks
Alex Graves, Abdel rahman Mohamed, and Geoffrey Hinton. 2013 · 2013
Earlier work this paper cites.
Meteor universal: Language specific translation evaluation for any target language
Michael Denkowski and Alon Lavie. 2014 · 2014
Earlier work this paper cites.
A convolutional neural network for modelling sentences
Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014 · 2014
Earlier work this paper cites.
Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timonthy Hirzel, Alan Aspuru-Guzik, and Ryan P Adams. 2015 · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Cited alongside, same era.
Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Generation from abstract meaning representation using tree transducers
Jeffrey Flanigan, Chris Dyer, Noah A. Smith, and Jaime Carbonell. 2016 · 2016
Cited alongside, same era.
Pointing the unknown words
Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, and Yoshua Bengio. 2016 · 2016
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling. 2016 · 2016
Cited alongside, same era.
Generating english from abstract meaning representations
Nima Pourdamghani, Kevin Knight, and Ulf Hermjakob. 2016 · 2016
Amr-to-text generation with synchronous node replacement grammar
Linfeng Song, Xiaochang Peng, Yue Zhang, Zhiguo Wang, and Daniel Gildea. 2017 · 2017
Later among the works it cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N.Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Graph-to-sequence learning using gated graph neural networks
Daniel Beck, Gholamreza Haffari, and Trevor Cohn. 2018 · 2018
Later among the works it cites.
Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani. 2018 · 2018
Later among the works it cites.
A graph-to-sequence model for AMR-to-text generation
Linfeng Song, Yue Zhang, Zhiguo Wang, and Daniel Gildea. 2018 · 2018
Later among the works it cites.
Factorising amr generation through syntax
Kris Cao and Stephen Clark. 2019 · 2019
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Cited alongside, same era.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Cited alongside, same era.
Opennmt: Open-source toolkit for neural machine translation
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander M. Rush. 2017 · 2017
Cited alongside, same era.
Neural AMR: Sequence-to-sequence models for parsing and generation
Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, and Luke Zettlemoyer. 2017 · 2017
Cited alongside, same era.
A structured self-attentive sentence embedding
Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
chrf++: words helping character n-grams
Maja Popović. 2017 · 2017
Cited alongside, same era.
Structural neural encoders for AMR-to-text generation
Marco Damonte and Shay B. Cohen. 2019 · 2019
Closest in time.
Modeling source syntax and semantics for neural amr parsing
DongLai Ge, Junhui Li, Muhua Zhu, and Shoushan Li. 2019 · 2019
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Densely connected graph convolutional networks for graph-to-sequence learning
Zhijiang Guo, Yan Zhang, Zhiyang Teng, and Wei Lu. 2019 · 2019
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Text generation from knowledge graphs with graph transformers
Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata, and Hannaneh Hajishirzi. 2019 · 2019
Closest in time.
Amr-to-text generation as a traveling salesman problem
Linfeng Song, Yue Zhang, Xiaochang Peng, Zhiguo Wang, and Daniel Gildea. 2016 · 2089
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