arxiv arXiv cs.AI · 51d ago · research

Efficient and Sound Probabilistic Verification for AI Agents

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A new framework enables secure, probabilistic policy enforcement for AI agents in ambiguous environments. It uses distributionally robust optimization to compute rigorous upper bounds on policy violation probabilities without assuming predicate independence. The method outperforms prior approaches on terminal and tool calling agent benchmarks, improving the security-utility trade-off.

Importance 3/3 Beats a top-lab benchmark New harness with differentiators arXiv cs.AI OpenAI Google DeepMind Mistral AI AI agents Evaluation & benchmarks Safety & alignment

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