发表机构
Instituto de Telecomunicações; National Technical University of Athens; Universidade de Lisboa; INESC-ID（电信研究所; 雅典国立技术大学; 里斯本大学; INESC-ID研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
ARCCS是首个全开源端到端监管合规检查系统，通过将法规分解为原子要求并结合证据与置信度进行评估，在GDPR评估中达96.67%一致性，在欧盟采购基准中达98.8%违规检测准确率。
AI 中文摘要
监管合规检查——判断目标文件是否满足法规义务——需要解读密集的法律文本、识别适用的条款，并将每项决策建立在明确的证据之上。我们提出ARCCS，一个端到端、自动化、智能体驱动且与具体法规无关的法律自然语言处理系统，用于合规检查。ARCCS将原始监管文本分解为原子化的、可追踪的要求，并利用检索到的证据、置信度分数和人类可解释的论证来评估目标文件是否符合这些要求。这种设计将合规评估与任何固定的监管模板或预定义规则集解耦，使流水线能够处理不同规模和结构的法规。我们在两个互补的场景中评估ARCCS。首先，在GDPR政策文件评估中，基于LLM的评审员发现其决策和论证在法律和证据上的一致性高达96.67%的评估案例。其次，在一个包含超过1200项单项规则检查的欧盟公共采购基准测试中，该系统在违规检测方面达到了98.8%的准确率。据我们所知，ARCCS是第一个完全开源的端到端监管合规检查及可审计报告生成系统。
英文摘要
Regulatory compliance checking - deciding whether a target document satisfies the obligations of a regulation - requires interpreting dense legal text, identifying which provisions apply, and grounding each decision in explicit evidence. We present ARCCS, an end-to-end, automated, agentic, and regulation-agnostic Legal NLP system for compliance checking. ARCCS decomposes raw regulatory text into atomic, traceable requirements and evaluates a target document against them using retrieved evidence, confidence scores, and human-interpretable justifications. This design decouples compliance assessment from any fixed regulatory template or predefined rule set, enabling the pipeline to operate over regulations of varying size and structure. We evaluate ARCCS in two complementary settings. First, in a GDPR policy-document evaluation, LLM-based judges find its decisions and justifications legally and evidentially consistent in up to 96.67% of the assessed cases. Second, on an EU public-procurement benchmark comprising more than 1,200 individual rule checks, the system attains 98.8% accuracy in violation detection. ARCCS is, to our knowledge, the first fully open-source system for end-to-end regulatory compliance checking and auditable report generation.
CommentsThis is the extended version of a paper accepted to EMNLP 2026 (System Demonstrations)
