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Ting Yan

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#artificial intelligence Preprint Oct 2026

CASEL: Consequence-Aware Selective Execution for Reliable Long-Horizon Tool-Using Agents

Tool-using language agents increasingly modify external systems, yet most runtime safeguards allocate scrutiny by generic uncertainty scores or coarse mutation heuristics. We introduce CASEL (Consequence-Aware Selective Execution Layer), a model-agnostic runtime allocation policy that combines calibrated failure probab...

Yan-Yan Zhang, Fei Shen, Ting Yan et al. · 0 citations
Review Aug 2026

When"Do Not"Is Not Deny: Security Rules in CLAUDE.md vs Built-In Controls

In CLAUDE.md,"do not"is a natural-language instruction that the model interprets. Claude Code's deny is a built-in control that blocks an action before the agent can take it. Both can express the same security goal, but they control the agent in different ways. We measure this gap in 481 public CLAUDE.md files. An LLM...

Ting Yan · 0 citations

Do User-Authored Permission Policies Improve Protection Against AI Agent Overreach?

A mechanism in which a language model maps actions to plain-language consequence categories with user-authored"allow","ask", or"never"rules is examined, and a gap between preference and commitment is revealed: repeatedly choosing "ask" preserves case-by-case choice but prevents a standing policy from settling decisions...

Ting Yan · 0 citations

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