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About this paper
Shayan Kiyani, Sima Noorani, George Pappas, Hamed Hassani
An external, distribution-free online algorithm, Strategic Oversight for Support-seeking (SOS), empowers AI agents to strategically determine when to seek external support. This approach reliably controls missed-support error at user-defined levels and substantially reduces the frequency of costly support calls across diverse agentic tasks and frontier LLMs.
Key insights
- The optimal support-seeking strategy at the population level is a threshold rule, where support is sought if its predicted value (likelihood of material benefit) exceeds a certain threshold.
- Rigorous finite-sample error control for missed-support can be achieved online and in a distribution-free manner through adaptive threshold adjustment based on observed outcomes.
- Online score calibration is crucial for improving the accuracy of predicting beneficial support over time, leading to more efficient resource utilization by reducing unnecessary support calls.
Summary by alphaXiv.
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