使用基于变压器的自然语言处理方法分析法律法庭文件之间的相似之处
Raphael Souza de Oliveira1,2, Erick Giovani Sperandio Nascimento2,3
1TRT5 - Regional Labour Court of the 5th Region, Salvador, Bahia, Brazil.
PloS one
|April 8, 2025
概括
人工智能 (AI) 和自然语言处理 (NLP) 加快了法律案件的处理. 像 LlaMA 这样的变压器模型在检测巴西司法程序中的法律文件相似性方面表现出卓越的表现.
科学领域:
- 计算语言学 计算语言学
- 人工智能在法律中的作用
- 自然语言处理自然语言处理.
背景情况:
- 司法系统面临的挑战是大量的法律文件.
- 自然语言处理 (NLP) 为管理法律数据提供了潜在的解决方案.
- 基于变压器的人工智能模型在各种NLP任务中表现有前途.
研究的目的:
- 评估基于变压器的NLP模型来检测司法文件之间的相似性.
- 在巴西法律背景下比较不同NLP技术的性能.
- 调查AI在加快司法程序中的应用.
主要方法:
- 采用了八种NLP技术,专注于变压器架构 (BERT,GPT-2,RoBERTa, LlaMA).使用了八种NLP技术,专注于变压器架构 (BERT,GPT-2,RoBERTa, LlaMA).
- 在巴西葡萄牙语的 corpora 上预先训练模型,并在 210,000 个法律案件中对它们进行了微调.
- 使用嵌入式生成文档向量表示,并通过等号距离评估相似性.
主要成果:
- 基于变压器的模型显著超过了传统的NLP技术.
- 针对法律领域进行微调的Llama模型在文档相似性检测方面取得了最高的准确性.
- 展示了分析大型法律文件数据集的强大方法.
结论:
- 变压器模型在法律领域的NLP任务中非常有效,特别是在文档相似性方面.
- 针对特定领域的微调模型,例如巴西法律,提高了性能.
- 这项研究促进了AI在法律中的应用,并支持可持续发展目标.
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