Fetching the paper…
Reading the bibliography…
We present Graformer, a novel Transformer-based encoder-decoder architecture for graph-to-text generation.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 1910
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
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.
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.
DBpedia: A nucleus for a web of open data
Sören Auer, Chris Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2008 · 2008
Earlier work this paper cites.
Algorithms for hyper-parameter optimization
James S. Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl. 2011 · 2011
Earlier work this paper cites.
Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel. 2016 · 2016
Earlier work this paper cites.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
Earlier work this paper cites.
The WebNLG challenge: Generating text from RDF data
Claire Gardent, Anastasia Shimorina, Shashi Narayan, and Laura Perez-Beltrachini. 2017 · 2017
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling. 2017 · 2017
Earlier work this paper cites.
Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, and Fei-Fei Li. 2017 · 2017
Earlier work this paper cites.
chrF++: words helping character n-grams
Maja Popović. 2017 · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Construction of the literature graph in semantic scholar
Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew Peters, Joanna Power, Sam Skjonsberg, Lucy Wang, Chris Wilhelm, Zheng Yuan, Madeleine van Zuylen, and Oren Etzioni. 2018 · 2018
Cited alongside, same era.
Generating fine-grained open vocabulary entity type descriptions
Rajarshi Bhowmik and Gerard de Melo. 2018 · 2018
Cited alongside, same era.
The best of both worlds: Combining recent advances in neural machine translation
Mia Xu Chen, Orhan Firat, Ankur Bapna, Melvin Johnson, Wolfgang Macherey, George Foster, Llion Jones, Mike Schuster, Noam Shazeer, Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Zhifeng Chen, Yonghui Wu, and Macduff Hughes. 2018 · 2018
Cited alongside, same era.
SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
Cited alongside, same era.
Deeper insights into graph convolutional networks for semi-supervised learning
Repulsive bayesian sampling for diversified attention modeling
Bang An, Xuannan Dong, and Changyou Chen. 2019 · 2019
Later among the works it cites.
Neural data-to-text generation: A comparison between pipeline and end-to-end architectures
Thiago Castro Ferreira, Chris van der Lee, Emiel van Miltenburg, and Emiel Krahmer. 2019 · 2019
Later among the works it cites.
Densely connected graph convolutional networks for graph-to-sequence learning
Zhijiang Guo, Yan Zhang, Zhiyang Teng, and Wei Lu. 2019 · 2019
Later among the works it cites.
Text Generation from Knowledge Graphs with Graph Transformers
Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata, and Hannaneh Hajishirzi. 2019 · 2019
Later among the works it cites.
Step-by-step: Separating planning from realization in neural data-to-text generation
Amit Moryossef, Yoav Goldberg, and Ido Dagan. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Qimai Li, Zhichao Han, and Xiao ming Wu. 2018 · 2018
Cited alongside, same era.
Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018 · 2018
Cited alongside, same era.
Deep graph convolutional encoders for structured data to text generation
Diego Marcheggiani and Laura Perez-Beltrachini. 2018 · 2018
Cited alongside, same era.
Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani. 2018 · 2018
Cited alongside, same era.
Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern. 2018 · 2018
Cited alongside, same era.
GTR-LSTM: A triple encoder for sentence generation from RDF data
Bayu Distiawan Trisedya, Jianzhong Qi, Rui Zhang, and Wei Wang. 2018 · 2018
Cited alongside, same era.
Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2018 · 2018
Cited alongside, same era.
DrugBank 5.0: a major update to the DrugBank database for 2018
David S Wishart, Yannick D Feunang, An C Guo, Elvis J Lo, Ana Marcu, Jason R Grant, Tanvir Sajed, Daniel Johnson, Carin Li, Zinat Sayeeda, Nazanin Assempour, Ithayavani Iynkkaran, Yifeng Liu, Adam Maciejewski, Nicola Gale, Alex Wilson, Lucy Chin, Ryan Cummings, Diana Le, Allison Pon, Craig Knox, and Michael Wilson. 2018 · 2018
Cited alongside, same era.
Emmanouil Antonios Platanios, Otilia Stretcu, Graham Neubig, Barnabas Poczos, and Tom Mitchell. 2019 · 2019
Later among the works it cites.
Enhancing AMR-to-text generation with dual graph representations
Leonardo F. R. Ribeiro, Claire Gardent, and Iryna Gurevych. 2019 · 2019
Later among the works it cites.
Modeling graph structure in transformer for better AMR-to-text generation
Jie Zhu, Junhui Li, Muhua Zhu, Longhua Qian, Min Zhang, and Guodong Zhou. 2019 · 2019
Later among the works it cites.
Graph transformer for graph-to-sequence learning
Deng Cai and Wai Lam. 2020 · 2020
Closest in time.
Geom-gcn: Geometric graph convolutional networks
Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang, Yu Lei, and Bo Yang. 2020 · 2020
Closest in time.
Modeling global and local node contexts for text generation from knowledge graphs
Leonardo F. R. Ribeiro, Yue Zhang, Claire Gardent, and Iryna Gurevych. 2020 · 2020
Closest in time.
An unsupervised joint system for text generation from knowledge graphs and semantic parsing
Martin Schmitt, Sahand Sharifzadeh, Volker Tresp, and Hinrich Schütze. 2020 · 2020
Closest in time.
Adaptive structural fingerprints for graph attention networks
Kai Zhang, Yaokang Zhu, Jun Wang, and Jie Zhang. 2020 · 2020
Closest in time.