Author

Xia Hu

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Preprint Aug 2026

SHE: Trajectory-driven Safety Harness Evolution for LLM Agents

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 safety-utility validation.

Wanying Qu, Qinghua Mao, Yu Li et al. · 1 citation

#artificial intelligence May 2026

SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces

This work presents SkillSafetyBench, a runnable benchmark for evaluating skill-facing safety failures, and suggests that agent safety depends not only on model-level alignment, but also on how agents interpret skills, trust workflow context, and act through executable environments.

Chang Jin, Anr'an W'ang, Zeming Wei et al. · arXiv.org · 11 citations · ⚡1