论文标题
填写Blanc：文档摘要的无人为质量估计
Fill in the BLANC: Human-free quality estimation of document summaries
论文作者
论文摘要
我们提出了Blanc，这是一种自动估算文档摘要质量的新方法。我们的目标是通过客观，可重复和完全自动化的方法来衡量摘要的功能性能。我们的方法通过衡量预先训练的语言模型获得的性能提升来实现这一目标，从而在文档文本上执行其语言理解任务，从而访问文档摘要。我们提供的证据表明，Blanc分数与人类评估的相关性与汇总质量测量的胭脂家族一样。与Rouge不同，Blanc方法不需要人工写的参考摘要，从而可以完全无人的摘要质量估计。
We present BLANC, a new approach to the automatic estimation of document summary quality. Our goal is to measure the functional performance of a summary with an objective, reproducible, and fully automated method. Our approach achieves this by measuring the performance boost gained by a pre-trained language model with access to a document summary while carrying out its language understanding task on the document's text. We present evidence that BLANC scores have as good correlation with human evaluations as do the ROUGE family of summary quality measurements. And unlike ROUGE, the BLANC method does not require human-written reference summaries, allowing for fully human-free summary quality estimation.
