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Safety in AI can now evolve from within the model itself, drastically enhancing long-term interaction capabilities without external constraints.
Attack rankings shift dramatically when evaluated under shared target-call budgets, revealing hidden efficiencies in traditional methods.
Attack strategies can now evolve and adapt in real-time, leading to a staggering 48.6-point improvement against state-of-the-art models.
Frontier LLMs can be induced to generate biologically hazardous sequences, with attack success rates reaching up to 100%.