Cited By
View all- Chen CHuang HChen HChen CHuang HChen H(2021)FinTech ApplicationsFrom Opinion Mining to Financial Argument Mining10.1007/978-981-16-2881-8_6(73-87)Online publication date: 21-May-2021
Learning to Generate Correct Numeric Values in News Headlines
Pages 17 - 18
Abstract
Motivated by the significant role of numeric values to convey concise and accurate information in news headlines, we focus the headline generation task on displaying correct numbers. We propose various ways to present the numeric values to the generative model. In the end, we come up with a simple but effective pre-train task to guide the generator to correctly process the values, which outperforms other base models even if the numbers in the headline are newly generated from the article.
References
[1]
Chung-Chi Chen, Hen-Hsen Huang, Hiroya Takamura, and Hsin-Hsi Chen. 2019. Numeracy-600K: Learning Numeracy for Detecting Exaggerated Information in Market Comments. In ACL.
[2]
Soichiro Murakami, Akihiko Watanabe, Akira Miyazawa, Keiichi Goshima, Toshihiko Yanase, Hiroya Takamura, and Yusuke Miyao. 2017. Learning to Generate Market Comments from Stock Prices. In ACL.
[3]
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner. 2019. Do NLP Models Know Numbers? Probing Numeracy in Embeddings. In Proceedings of the 2019 Conference on EMNLP-IJCNLP.
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- Learning to Generate Correct Numeric Values in News Headlines
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Published In
April 2020
854 pages
ISBN:9781450370240
DOI:10.1145/3366424
Copyright © 2020 ACM.
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Published: 20 April 2020
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WWW '20
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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%
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Cited By
View all- Chen CHuang HChen HChen CHuang HChen H(2021)FinTech ApplicationsFrom Opinion Mining to Financial Argument Mining10.1007/978-981-16-2881-8_6(73-87)Online publication date: 21-May-2021
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