This work identifies and formalizes this failure mode, which is term destructive resource preemption: obtaining the resources required for a requested task by terminating, overwriting, evicting, or degrading an incumbent task.
Through harness-policy co-evolution, SafeEvolve converts safety experience into an evolved runtime harness and improved policy behavior, and experiments show that SafeEvolve achieves a stronger safety-utility tradeoff than existing baselines.
Safety Harness Evolution (SHE) is proposed, a framework that learns evolving safe boundaries from rollout trajectories and introduces an attribution-guided evolution loop that converts trajectory failures into structured diagnoses, learns artifact-specific boundary refinements, and selects evolved harnesses through saf...
Wanying Qu, Qing-Hua Mao, Yu Li et al.· 5 citations
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