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Law Stack Exchange

Introduced by Jonathan Li et al. in Parameter-Efficient Legal Domain Adaptation25 Oct 2022 archive 2025-07-28

Description

Dataset from the Law Stack Exchange, as used in "Parameter-Efficient Legal Domain Adaptation" (Li et al., 2022). We introduce a dataset with data from the Law Stack Exchange. This dataset is composed of questions from the Law Stack Exchange, which is a community forum-based website containing questions with answers to legal questions. We link the questions with their associated tags (e.g., "copyright" or "criminal-law"), and perform a multi-label classification task

Citation Information

@inproceedings{li-etal-2022-parameter,
    title = "Parameter-Efficient Legal Domain Adaptation",
    author = "Li, Jonathan  and
      Bhambhoria, Rohan  and
      Zhu, Xiaodan",
    booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2022",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.nllp-1.10",
    pages = "119--129",
}

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY-SA 3.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • Law Stack Exchange

1 variant name, as the archive lists them.

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