SAFETY SENTRY: Context-Aware Human Intervention via EXECUTE-ASK-REFUSE Routing
LLM agents act on real-world environments through tool calls, and a single misjudged action can cause irreversible harm. The standard safeguard is a guard model that labels each proposed action as safe or unsafe, but this binary view conflates two distinct decisions: whether the action is harmful in itself, and whether it is appropriate given the user's context. It also operates at the granularity of action categories rather than individual instances, producing routine interruptions that erode autonomy and train users to wave through the most consequential alerts. We reframe the problem as a per-instance three-way routing decision over {EXECUTE, ASK, REFUSE} and instantiate it with Safety...
| Authors | Tianyu Chen, Chujia Hu, Wenjie Wang |
|---|---|
| Primary category | cs.AI |
| Published | 15 July 2026 |
| Last updated at source | 8 October 2026 |
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