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Yanwei Fu

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#artificial intelligence Preprint Sep 2026

ClashBench: Conflicts Leading Agents to Seize and Harm

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.

Yue-Jin Xie, Yu Li, Da-Di Guo et al. · 1 citation · ⚡1
#artificial intelligence Preprint Sep 2026

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

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.

Qing-Hua Mao, Wanying Qu, Da-Di Guo et al. · 6 citations · ⚡2
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

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