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Kamalika Chaudhuri

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Preprint Oct 2026

InferPriv: Evaluating Inferential Privacy Leakage in LLM Assistants

A benchmark that measures whether an honest-but-curious recipient can infer a user's sensitive attributes from an LLM's reply on routine task is introduced, and it is found that inferential leakage substantially exceeds direct leakage across models and prompts.

Peng Huang, Yi-Wei Fu, Luo-Xi Meng et al. · 0 citations

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