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Safety Paradox: How Enhanced Safety Awareness Leaves LLMs Vulnerable to Posterior Attack

This work formalizes the Safety Paradox, analytically showing that monotonic improvements in safety alignment naturally amplify posterior vulnerability, and establishes a causal link via reinforcement learning interventions, exemplifying that artificially degrading a model's safety judgment immunizes it against the att...

Ho-Ang P. Long, H. V. Le, Shaoyang Xu et al. · 0 citations

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