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CAMIA presents a privacy-focused attack that probes AI models to reveal what information they memorize from training data, raising concerns about inadvertent retention of sensitive content. The method underscores risks of data leakage and emphasizes the need for tighter controls around dataset handling, evaluation, and deployment of large-scale models.