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ActGov: Governing LLM Agent Actions via Policy-Constrained Validation

Large language model (LLM) agents increasingly execute long-horizon workflows through external tools, allowing untrusted outputs to influence subsequent actions and exceed user authorization. Existing defenses isolate injected content or constrain execution with predefined plans and static policies, but these approaches are brittle under dynamic workflows and scale poorly across extensible tool…

We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.

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