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Learning to Generate Correct Numeric Values in News Headlines

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Published:20 April 2020Publication History

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.Google ScholarGoogle Scholar
  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.Google ScholarGoogle Scholar
  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.Google ScholarGoogle ScholarCross RefCross Ref

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          • Published in

            cover image ACM Conferences
            WWW '20: Companion Proceedings of the Web Conference 2020
            April 2020
            854 pages
            ISBN:9781450370240
            DOI:10.1145/3366424

            Copyright © 2020 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 20 April 2020

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            • research-article
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            • Refereed limited

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            Overall Acceptance Rate1,899of8,196submissions,23%

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            The ACM Web Conference 2024
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