AutoRISE evolves red-teaming attack strategies as editable executable programs via an agent, yielding 17-point higher average attack success rates than baselines across 11 models.
Read the agent diagnostics carefully: per-technique success rates, per-category breakdowns, and judge rationales should drive your edit choice
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AutoRISE: Agent-Driven Strategy Evolution for Red-Teaming Large Language Models
AutoRISE evolves red-teaming attack strategies as editable executable programs via an agent, yielding 17-point higher average attack success rates than baselines across 11 models.