AI RESEARCH
ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance
arXiv CS.CL
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ArXi:2604.12308v1 Announce Type: new Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires reasoning about the context to identify and mitigate potential risks. Though researchers have widely explored using large language models (LLMs) as evaluators for contextualized safety and privacy assessments, these efforts typically assume the availability of complete and clear context, whereas real-world contexts tend to be ambiguous and incomplete.