Web: http://arxiv.org/abs/2005.06377

May 6, 2022, 1:11 a.m. | Forrest Sheng Bao, Hebi Li, Ge Luo, Minghui Qiu, Yinfei Yang, Youbiao He, Cen Chen

cs.CL updates on arXiv.org arxiv.org

Canonical automatic summary evaluation metrics, such as ROUGE, focus on
lexical similarity which cannot well capture semantics nor linguistic quality
and require a reference summary which is costly to obtain. Recently, there have
been a growing number of efforts to alleviate either or both of the two
drawbacks. In this paper, we present a proof-of-concept study to a weakly
supervised summary evaluation approach without the presence of reference
summaries. Massive data in existing summarization datasets are transformed for
training by …

arxiv negative sampling summarization

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