arXiv: cs.AI preprintsInternational6 November 2026
Agentic Abstention: Do Agents Know When to Stop Instead of Act?
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arXiv:2606.28733v2 Announce Type: replace Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and tools to complete user goals. Yet not every goal is well specified or achievable in an available environment. In such cases, a reliable agent should recognize that further interaction is unlikely to help and abstain from additional tool calls. We define Agentic Abstention, the problem of deciding when an agent should stop acting under uncertainty. Unlike standard LLM abstention, which is usually evaluated as a single-turn answer-or-abstain decision, age
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