Contextual Candour: Role-Aware Graduated Disclosure for LLMs over Mixed-Sensitivity Contexts
Research proposes role-aware graduated disclosure for LLMs operating over mixed-sensitivity data, replacing binary access-control filters with context-sensitive information release — relevant for enterprises handling classified tiers of data within a single AI system.
Summary written by editorial AI · Source link below
arXiv:2610.28067v1 Announce Type: new Abstract: LLMs increasingly operate over mixed-sensitivity contexts, where they must reason over information ranging from public to confidential while disclosing only what the user is authorised to receive. Existing approaches enforce access control as a binary decision: either fully answering or refusing, without regulating how much or what kind of information is revealed if access is granted, leading to over-refusal or unintended leakage. We introduce gra
Editorial Analysis
Enterprises running LLMs across multiple data-classification tiers risk oversharing if access controls remain binary; graduated disclosure aligns AI output with need-to-know principles.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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