Papers › Sensitivity of BLANC to human-scored qualities of text summaries

Sensitivity of BLANC to human-scored qualities of text summaries

13 Oct 2020arXiv:2010.06716archive 2025-07-28

Oleg Vasilyev, Vedant Dharnidharka, Nicholas Egan, Charlene Chambliss, John Bohannon

We explore the sensitivity of a document summary quality estimator, BLANC, to human assessment of qualities for the same summaries. In our human evaluations, we distinguish five summary qualities, defined by how fluent, understandable, informative, compact, and factually correct the summary is. We make the case for optimal BLANC parameters, at which the BLANC sensitivity to almost all of summary qualities is about as good as the sensitivity of a human annotator.

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PrimerAI/blanc officialmentioned in papermentioned on GitHubpytorchMIT report

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