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TrustJev: Separating Policy Authority from Untrusted Evidence in LLM-Based Decisions
Decision models enable software to select from predefined actions using natural language inputs. However, the external evidence that supplies facts for these decisions may also contain instructions that attempt to override the application's policy. We propose TrustJev, a framework combining protecte
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