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Automatic construction of relevant Knowledge Bases (KBs) from text, and generation of semantically meaningful text from KBs are both long-standing goals in Machine Learning.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams. 1992 · 1992
Earlier work this paper cites.
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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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2016 · 2016
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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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chrF++: words helping character n-grams
Maja Popović. 2017 · 2017
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Self-critical sequence training for image captioning
Steven J Rennie, Etienne Marcheret, Youssef Mroueh, Jerret Ross, and Vaibhava Goel. 2017 · 2017
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Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto. 2018 · 2018
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Machine translation aided bilingual data-to-text generation and semantic parsing
Oshin Agarwal, Mihir Kale, Heming Ge, Siamak Shakeri, and Rami Al-Rfou. 2020 · 2020
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The 2020 bilingual, bi-directional WebNLG+ shared task: Overview and evaluation results (WebNLG+ 2020)
Thiago Castro Ferreira, Claire Gardent, Nikolai Ilinykh, Chris van der Lee, Simon Mille, Diego Moussallem, and Anastasia Shimorina. 2020a · 2020
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Reinforcement learning based graph-to-sequence model for natural question generation
Yu Chen, Lingfei Wu, and Mohammed J. Zaki. 2020 · 2020
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DualTKB: A Dual Learning Bridge between Text and Knowledge Base
Pierre Dognin, Igor Melnyk, Inkit Padhi, Cicero Nogueira dos Santos, and Payel Das. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Automatic Myanmar image captioning using CNN and LSTM-based language model
San Pa Pa Aung, Win Pa Pa, and Tin Lay Nwe. 2020 · 2020
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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. 2020 · 2020
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Investigating pretrained language models for graph-to-text generation
Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, and Iryna Gurevych. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Leveraging large pretrained models for WebNLG 2020
Xintong Li, Aleksandre Maskharashvili, Symon Jory Stevens-Guille, and Michael White. 2020 · 2020
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A better variant of self-critical sequence training
Ruotian Luo. 2020 · 2020
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Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+) . Association for Computational Linguistics, Dublin, Ireland (Virtual)
Thiago Castro Ferreira, Claire Gardent, Nikolai Ilinykh, Chris van der Lee, Simon Mille, Diego Moussallem, and Anastasia Shimorina, editors. 2020b
Cited in the paper.
𝓅 2 {\mathcal{p}^{2}} : A plan-and-pretrain approach for knowledge graph-to-text generation
Qipeng Guo, Zhijing Jin, Ning Dai, Xipeng Qiu, Xiangyang Xue, David Wipf, and Zheng Zhang. 2020a
Cited in the paper.
CycleGT: Unsupervised graph-to-text and text-to-graph generation via cycle training
Qipeng Guo, Zhijing Jin, Xipeng Qiu, Weinan Zhang, David Wipf, and Zheng Zhang. 2020b
Cited in the paper.
Zixiaofan Yang, Arash Einolghozati, Hakan Inan, Keith Diedrick, Angela Fan, Pinar Donmez, and Sonal Gupta. 2020 · 2020
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Knowledge graph based synthetic corpus generation for knowledge-enhanced language model pre-training
Oshin Agarwal, Heming Ge, Siamak Shakeri, and Rami Al-Rfou. 2021 · 2021
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