mse30/ReflectSumm

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The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at 8558691
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Citation text from the card

@inproceedings{elaraby-etal-2024-reflectsumm-benchmark,
    title = "{R}eflect{S}umm: A Benchmark for Course Reflection Summarization",
    author = "Elaraby, Mohamed  and
      Zhong, Yang  and
      Litman, Diane  and
      Butt, Ahmed Ashraf  and
      Menekse, Muhsin",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1207",
    pages = "13819--13846",
    abstract = "This paper introduces ReflectSumm, a novel summarization dataset specifically designed for summarizing students{'} reflective writing. The goal of ReflectSumm is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization domain in general and the educational domain in particular. The dataset encompasses a diverse range of summarization tasks and includes comprehensive metadata, enabling the exploration of various research questions and supporting different applications. To showcase its utility, we conducted extensive evaluations using multiple state-of-the-art b

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dataset_licence({ "id": "mse30/ReflectSumm" })
signal: "permissive"
stated_licence: "mit"
sources: 0