Datasets:
Tasks:
Fill-Mask
Sub-tasks:
masked-language-modeling
Languages:
English
Size:
10M<n<100M
ArXiv:
License:
Update README.md
Browse files
README.md
CHANGED
@@ -195,32 +195,13 @@ We mainly focus on U.S. and English-speaking legal sources, though we include so
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For a citation to this work:
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```
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# EurLex
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@inproceedings{chalkidis-etal-2019-large,
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title = "Large-Scale Multi-Label Text Classification on {EU} Legislation",
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author = "Chalkidis, Ilias and Fergadiotis, Manos and Malakasiotis, Prodromos and Androutsopoulos, Ion",
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booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
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year = "2019",
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address = "Florence, Italy",
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publisher = "Association for Computational Linguistics",
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url = "https://www.aclweb.org/anthology/P19-1636",
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doi = "10.18653/v1/P19-1636",
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pages = "6314--6322"
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}
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@inproceedings{huang2021context,
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title={Context-aware legal citation recommendation using deep learning},
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author={Huang, Zihan and Low, Charles and Teng, Mengqiu and Zhang, Hongyi and Ho, Daniel E and Krass, Mark S and Grabmair, Matthias},
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booktitle={Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law},
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pages={79--88},
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year={2021}
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}
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```
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```
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@article{hendersonkrass2022pileoflaw,
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title={Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset},
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author={Henderson*, Peter and Krass*, Mark and Zheng, Lucia and Guha, Neel and Manning, Christopher and Jurafsky, Dan and Ho, Daniel E},
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journal={arXiv preprint arXiv:2204.11910},
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year={2022}
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}
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```
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Since this dataset also includes several other data sources with citations, please refer to our paper and cite the additional relevant work in addition to our own work.
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