Papers with LEGAL-BERT

2 papers
LEGAL-BERT: The Muppets straight out of Law School (2020.findings-emnlp)

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Challenge: Existing guidelines for pre-training and fine-tuning do not always generalize well in the legal domain.
Approach: They propose to use BERT out of the box, adapt it by additional pre-training on domain-specific corpora, and pre-train it from scratch on domains.
Outcome: The proposed strategies are: use the original BERT out of the box, adapt it by additional pre-training on domain-specific corpora, and pre-train it from scratch on domain specific corpors.
Modeling Legal Reasoning: LM Annotation at the Edge of Human Agreement (2023.emnlp-main)

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Challenge: Existing research examines simple classification tasks, but ability of LMs to classify on complex tasks is less well understood.
Approach: They analyze a Supreme Court opinion annotated by a team of domain experts . they find generative models perform poorly when given instructions equal to human annotators .
Outcome: The proposed model performs poorly when given instructions equal to instructions given to human annotations . strongest results derive from fine-tuning models on the annotated dataset .

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