bltlab/lr-sum

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The declared licence (cc-by-4.0) is classified as permissive.

Declared licence: cc-by-4.0, from the tagEvidence: README.md at deb2e73
Licence files: No licence file at the top level of the repositoryEvidence: file list at deb2e73
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Citation text from the card

@inproceedings{palen-michel-lignos-2023-lr,
    title = "{LR}-Sum: Summarization for Less-Resourced Languages",
    author = "Palen-Michel, Chester  and
      Lignos, Constantine",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.427",
    doi = "10.18653/v1/2023.findings-acl.427",
    pages = "6829--6844",
    abstract = "We introduce 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 abstractive and extractive summarization experiments to establish baselines and discuss the limitations of this dataset.",
}

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dataset_licence({ "id": "bltlab/lr-sum" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0