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Embodied Robotics and Automation Lab , University of South Florida , Tampa , FL , USA
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Bidirectional, change-sensitive memory updates unlock near-perfect recall across megabytes of context, even when trained on much shorter sequences.
LLMs leak training data membership through subtle, gradient-induced shifts in their internal representations, enabling a surprisingly effective new attack.