English

LR-Sum: Summarization for Less-Resourced Languages

Computation and Language 2023-10-30 v2

Abstract

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.

Keywords

Cite

@article{arxiv.2212.09674,
  title  = {LR-Sum: Summarization for Less-Resourced Languages},
  author = {Chester Palen-Michel and Constantine Lignos},
  journal= {arXiv preprint arXiv:2212.09674},
  year   = {2023}
}
R2 v1 2026-06-28T07:42:48.864Z