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Jing-Ping Wang

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#artificial intelligence Review Oct 2026

When Agents Fail: Model or Harness--Who's to Blame?

LLM agents combine models with execution harnesses, so agentic benchmark performance reflects their joint behavior. We argue that harnesses should therefore be evaluated through their interactions with underlying models. We develop a framework combining five complementary measures: (i) Valid Completion Rate (VCR), how...

Shao Zhang, Hang-Fan Zhang, Yuan-Yuan Shi et al. · 0 citations
Sep 2026

MetaPermit: Scalable and Auditable Access Control for AI Agents via LLM-Inferred Meta-Attributes

The results show that MetaPermit produces 31% more consistent authorization decisions than LLM-driven authorization and outperforms the state-of-the-art defenses CaMeL and IPIGuard in both task completion and robustness to IPI attacks, with no malicious tool calls executed.

Han-Zhang Ma, Alicia Y. Hariri, Tian-Xiang Shen et al. · 0 citations

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