MichaelR207/MultiSimV2

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The declared licence (mit) is classified as permissive.

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@inproceedings{ryan-etal-2023-revisiting,
    title = "Revisiting non-{E}nglish Text Simplification: A Unified Multilingual Benchmark",
    author = "Ryan, Michael  and
      Naous, Tarek  and
      Xu, Wei",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-long.269",
    pages = "4898--4927",
    abstract = "Recent advancements in high-quality, large-scale English resources have pushed the frontier of English Automatic Text Simplification (ATS) research. However, less work has been done on multilingual text simplification due to the lack of a diverse evaluation benchmark that covers complex-simple sentence pairs in many languages. This paper introduces the MultiSim benchmark, a collection of 27 resources in 12 distinct languages containing over 1.7 million complex-simple sentence pairs. This benchmark will encourage research in developing more effective multilingual text simplification models and evaluation metrics. Our experiments using MultiSim with pre-trained multilingual language models reveal exciting performance improvements from multilingual training in non-English settings. We observe strong performance from Russian in zero-shot cross-lingual transfer to low-resource languages. We further show that few-shot prompt

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dataset_licence({ "id": "MichaelR207/MultiSimV2" })
signal: "permissive"
stated_licence: "mit"
sources: 0