Elliot Amponsah

The paper systematically evaluates eight privacy-preserving techniques for LLM requests, finding that a combination of local inference, redaction, and semantic rephrasing provides the best overall protection.

The paper introduces a geometry-aware framework for quantum differential privacy by aligning noise to the Quantum Fisher Information (QFI) eigenstructure, achieving significantly tighter privacy-utility bounds than classical methods.