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Dongrui Liu

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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
Conference Open access Jul 2026

AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments

AgentGym2 is presented, a new evaluation framework with task instances grounded in real-world end-to-end working demands that measures agents'ability to execute end-to-end procedures, discover tools via exploration, compose tools for unseen tasks, and remain robust to noisy and underspecified information.

Zhiheng Xi, Dingwen Yang, Jiaqi Liu et al. · 1 citation