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Logical Natural Language Generation, i.e., generating textual descriptions that can be logically entailed by a structured table, has been a challenge due to the low fidelity of the generation.
Pytorch: An imperative style, high-performance deep learning library
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Bleu: a method for automatic evaluation of machine translation
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CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training
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The E2E Dataset: New Challenges For End-to-End Generation
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Tang, D.; Duan, N.; Qin, T.; Yan, Z.; and Zhou, M. 2017 · 2017
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
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Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
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Edunov, S.; Ott, M.; Auli, M.; and Grangier, D. 2018 · 2018
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Hoang, V. C. D.; Koehn, P.; Haffari, G.; and Cohn, T. 2018 · 2018
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Transformers: State-of-the-Art Natural Language Processing
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Xu, W.; Niu, X.; and Carpuat, M. 2020 · 2020
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SQL-to-Text Generation with Graph-to-Sequence Model
Xu, K.; Wu, L.; Wang, Z.; Feng, Y.; and Sheinin, V. 2018 · 2018
Cited alongside, same era.
Joint training for neural machine translation models with monolingual data
Zhang, Z.; Liu, S.; Li, M.; Zhou, M.; and Chen, E. 2018 · 2018
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Semi-Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
Qader, R.; Portet, F.; and Labbé, C. 2019 · 2019
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Language Models are Unsupervised Multitask Learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
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Dynamic Data Selection and Weighting for Iterative Back-Translation
Dou, Z.-Y.; Anastasopoulos, A.; and Neubig, G. 2020 · 2020
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Filtering Back-Translated Data in Unsupervised Neural Machine Translation
Khatri, J.; and Bhattacharyya, P. 2020 · 2020
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Logical Natural Language Generation from Open-Domain Tables
Chen, W.; Chen, J.; Su, Y.; Chen, Z.; and Wang, W. Y. 2020a
Cited in the paper.
BERTScore: Evaluating Text Generation with BERT
Zhang, T.; Kishore, V.; Wu, F.; Weinberger, K. Q.; and Artzi, Y. 2020 · 2020
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Jointly Improving Language Understanding and Generation with Quality-Weighted Weak Supervision of Automatic Labeling
Chang, E.; Demberg, V.; and Marin, A. 2021 · 2021
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Neural Data-to-Text Generation with LM-based Text Augmentation
Chang, E.; Shen, X.; Zhu, D.; Demberg, V.; and Su, H. 2021 · 2021
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Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization
Guo, Y.; Zhu, H.; Lin, Z.; Chen, B.; Lou, J.-G.; and Zhang, D. 2021 · 2021
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De-Confounded Variational Encoder-Decoder for Logical Table-to-Text Generation
Wenqing, C.; Jidong, T.; Yitian, L.; Hao, H.; and Yaohui, J. 2021 · 2021
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Logic2Text: High-Fidelity Natural Language Generation from Logical Forms
Chen, Z.; Chen, W.; Zha, H.; Zhou, X.; Zhang, Y.; Sundaresan, S.; and Wang, W. Y. 2020b · 2096
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