Abstract
This research explores the application of Large Language Models (LLMs) for automating the extraction of requirement-related legal content in the food safety domain and checking legal compliance of regulatory artifacts. With Industry 4.0 revolutionizing the food industry and with the General Data Protection Regulation (GDPR) reshaping privacy policies and data processing agreements, there is a growing gap between regulatory analysis and recent technological advancements. This study aims to bridge this gap by leveraging LLMs, namely BERT and GPT models, to accurately classify legal provisions and automate compliance checks. Our findings demonstrate promising results, indicating LLMs' significant potential to enhance legal compliance and regulatory analysis efficiency, notably by reducing manual workload and improving accuracy within reasonable time and financial constraints.
Abstract (translated)
这项研究探讨了在食品安全领域应用大型语言模型（LLMs）自动提取相关法律内容以及检查法规文件的法律合规性。随着工业4.0的颠覆性以及《通用数据保护条例》（GDPR）对隐私政策和个人数据处理协议的重新塑造，法规分析和最近的技术进步之间的差距越来越大。本研究旨在通过利用LLMs（如BERT和GPT模型）准确分类法律条文并自动检查合规性，从而弥合这一差距。我们的研究结果表明，LLMs显著增强法律合规性和法规分析效率，特别是在降低手动工作负担和提高准确性方面。
URL
https://arxiv.org/abs/2404.17522
