A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs
The advent of LLMs has significantly changed the research on privacy policy and data compliance analysis by enabling tasks that previously required specialized, domain-specific tools. However, it remains unclear to what extent LLMs can truly replicate the diverse functionalities, and the wide range of methodologies and analysis offered by prior work. In this paper, we conduct the first systematic evaluation of whether off-the-shelf LLMs can replace specialized privacy analysis tools. We study six representative tools spanning three major functionalities: contradiction detection, regulatory com
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- PossiblePossibly related (embedding) · 48%Governance AI study finds EU data protection rules delay 11% of LLM releases - Crypto Briefing →
- PossiblePossibly related (embedding) · 46%Multi-tenant LLM analytics with row-level security: How we built a secure agent on AWS →
- FuzzySimilar title/name (fuzzy) · 59%ikaijua/Awesome-AITools →
“Fuzzy title match (0.73): “A Systematic Evaluation of Traditional Privacy Policy Analys” ≈ “ikaijua/Awesome-AITools””
- LinkedLinked via arxiv author · 85%Madhav Aryal →
“A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs”
- LinkedLinked via arxiv author · 85%Sudipa Saha →
“A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs”
- LinkedLinked via arxiv author · 85%Kaushal Kafle →
“A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs”
- LinkedLinked via arxiv author · 85%Anshuman Chhabra →
“A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs”
- LinkedLinked via arxiv author · 85%Sunil Manandhar →
“A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs”