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., Nigel (1)
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Hits 1 – 5 of 5
1
Plan-then-Generate: Controlled Data-to-Text Generation via Planning ...
Su, Yixuan
;
Vandyke, David
;
Wang, Sihui
;
Fang, Yimai
;
Collier, Nigel
. - : arXiv, 2021
Abstract:
Recent developments in neural networks have led to the advance in data-to-text generation. However, the lack of ability of neural models to control the structure of generated output can be limiting in certain real-world applications. In this study, we propose a novel Plan-then-Generate (PlanGen) framework to improve the controllability of neural data-to-text models. Extensive experiments and analyses are conducted on two benchmark datasets, ToTTo and WebNLG. The results show that our model is able to control both the intra-sentence and inter-sentence structure of the generated output. Furthermore, empirical comparisons against previous state-of-the-art methods show that our model improves the generation quality as well as the output diversity as judged by human and automatic evaluations. ... : Accepted to Findings of EMNLP 2021 ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://dx.doi.org/10.48550/arxiv.2108.13740
https://arxiv.org/abs/2108.13740
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2
Plan-then-Generate: Controlled Data-to-Text Generation via Planning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Nigel
;
Fang, Yimai
. - : Underline Science Inc., 2021
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3
A Generative Model for Joint Natural Language Understanding and Generation ...
Tseng, Bo-Hsiang
;
Cheng, Jianpeng
;
Fang, Yimai
. - : arXiv, 2020
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4
Proposition-based summarization with a coherence-driven incremental model ...
Fang, Yimai
. - : Apollo - University of Cambridge Repository, 2019
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5
Proposition-based summarization with a coherence-driven incremental model
Fang, Yimai
. - : University of Cambridge, 2018. : Computer Science and Technology, 2018. : Hughes Hall, 2018
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