Author

Dongrui Liu

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#artificial intelligence Preprint Sep 2026

SafeEvolve: Harness-Policy Co-Evolution from Agent Experience for Safety Alignment

The performance of LLM-based agents is jointly shaped by the base model and the harness used when interacting with the environment. This exposes them to safety risks in both harmful final responses and multi-step execution trajectories. Existing safety alignment mechanisms often rely on either external harness updates...

Qing-Hua Mao, Wanying Qu, Da-Di Guo et al. · 1 citation

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 saf...

Wanying Qu, Qing-Hua Mao, Yu Li et al. · 5 citations