Conditional Marginal Gain (CMG) is a metric used in privacy attacks on Retrieval-Augmented Generation (RAG) systems to quantify the expected increase in sensitive information exfiltrated by a new query. It enables principled, long-term planning for adversaries under uncertainty.
Conditional Marginal Gain (CMG) is a metric used by attackers to strategically exfiltrate sensitive data from RAG systems. It helps them plan queries to maximize the amount of new information gained, enabling a more effective, long-term data extraction strategy compared to ad-hoc methods.
CMG
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