SOURCE-LINKED INTELLIGENCE
PASTABench: Proactive Assessment of Sequential Trajectories for Agent Safety
As Large Language Models (LLMs) evolve into autonomous agents that alter real-world states, ensuring operational safety across multi-step workflows has become a critical challenge. While recent work has moved beyond single-turn evaluation toward multi-turn paradigms, key limitations persist: step-level methods treat actions in isolation, missing how risks accumulate, while trajectory-level evaluations operate post-hoc, offering no opportunity for timely intervention. To address these limitations, we formalize Decoupled Proactive Safety Monitoring along three dimensions: whether to intervene, w
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T14:34:45.000Z
First collected: 2026-09-24T08:22:30.429Z. This is not the publication date.