ContextLeak is the first empirical framework to audit worst-case information leakage in private in-context learning by inserting identifiable canary tokens and measuring their presence in model outputs.
A.6 Experimental Settings + Parameters For classification tasks, we utilize the SubJ dataset (Pang and Lee, 2004) and Sarcasm detection (Kho- dak et al., 2018)
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ContextLeak: Auditing Leakage in Private In-Context Learning Methods
ContextLeak is the first empirical framework to audit worst-case information leakage in private in-context learning by inserting identifiable canary tokens and measuring their presence in model outputs.