45 citations · 125 across the 9 of their papers we have counts for
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cs.CL2023★ 4 cited
MultiLegalPile: A 689GB Multilingual Legal Corpus
Joel Niklaus, Veton Matoshi, Matthias Stürmer +2
Large, high-quality datasets are crucial for training Large Language Models (LLMs). However, so far, there are few datasets available for specialized critical domains such as law a…
cs.CL2021★ 14 cited
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset
Lucia Zheng, Neel Guha, Brandon R. Anderson +2
While self-supervised learning has made rapid advances in natural language processing, it remains unclear when researchers should engage in resource-intensive domain-specific pretr…