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System Switch: When Should a Fast Decision Model Stop and Think?

This paper explores when a fast decision model should switch to a slower reasoning model. The study uses a fast actor paired with a reasoning vision-language model, tested in closed-loop Doom and the System One decision models. Results show that deferring the least confident 30% of decisions to the reasoning model improves performance, with gains proportional to the actor's AUROC. However, in closed-loop scenarios, no variant reached the exit, and the reasoning model faced challenges in distinguishing locked doors without prior knowledge.

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PublishedOctober 7, 2026Gian Luca Bailo
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WHY IT MAY MATTER

This research helps determine optimal points for switching between fast and slow decision-making processes, which is crucial for applications requiring real-time responses and accurate reasoning, such as robotics and AI-driven systems.

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