AI RESEARCH
Human-Guided Harm Recovery for Computer Use Agents
arXiv CS.AI
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ArXi:2604.18847v1 Announce Type: new As LM agents gain the ability to execute actions on real computer systems, we need ways to not only prevent harmful actions at scale but also effectively remediate harm when prevention fails. We formalize a solution to this neglected challenge in post-execution safeguards as harm recovery: the problem of optimally steering an agent from a harmful state back to a safe one in alignment with human preferences.