论文标题
LR-SUM：汇总较少的语言
LR-Sum: Summarization for Less-Resourced Languages
论文作者
论文摘要
该预印刷描述了在LR-SUM上正在进行的工作，LR-SUM是一种新的允许许可的数据集，目的是为较低的语言提供自动摘要的进一步研究。 LR-SUM包含40种语言的人写的摘要，其中许多语言的资源较低。我们描述了从多语言开放文本语料库中提取和过滤数据集的过程（Palen-Michel等，2022）。源数据是从美国语音网站收集的公共领域新闻，LR-SUM是根据Creative Commons许可证（CC By 4.0）发布的，使其成为最公开许可的多语言摘要数据集之一。我们描述了如何计划将数据用于建模实验并讨论数据集的局限性。
This preprint describes work in progress on LR-Sum, a new permissively-licensed dataset created with the goal of enabling further research in automatic summarization for less-resourced languages. LR-Sum contains human-written summaries for 40 languages, many of which are less-resourced. We describe our process for extracting and filtering the dataset from the Multilingual Open Text corpus (Palen-Michel et al., 2022). The source data is public domain newswire collected from from Voice of America websites, and LR-Sum is released under a Creative Commons license (CC BY 4.0), making it one of the most openly-licensed multilingual summarization datasets. We describe how we plan to use the data for modeling experiments and discuss limitations of the dataset.
