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",
}
Papers
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