De Jure: Iterative LLM Self-Refinement for Structured Extraction of Regulatory Rules

This research introduces "De Jure," a system for iterative self-refinement of Large Language Models (LLMs) to accurately extract structured regulatory rules from legal texts. This has immense real-world potential for automating compliance checks, legal research, and policy analysis, significantly reducing manual effort and improving accuracy in highly regulated industries.