We present PeerSum, a new MDS dataset using peer reviews of scientific publications. Our dataset differs from the existing MDS datasets in that our summaries (i.e., the meta-reviews) are highly abstractive and they are real summaries of the source documents (i.e., the reviews) and it also features disagreements among source documents. We found that current state-of-the-art MDS models struggle to generate high-quality summaries for PeerSum, offering new research opportunities.
翻译:我们利用对科学出版物的同行审查来介绍新的MDS数据集PeerSum。 我们的数据集与现有的MDS数据集不同,因为我们的摘要(即元审查)非常抽象,它们是原始文件(即审查)的真实摘要,而且源文件之间也存在分歧。 我们发现,目前最先进的MDS模型正在努力为PealSum生成高质量的摘要,提供了新的研究机会。