AI

The First Few Tokens Matter: Understanding Chain-of-Thought Controllability

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Briefings

Research on arXiv:2610.40939v1 reveals that Chain-of-Thought (CoT) monitoring fails due to an entropy collapse in the first few tokens after the opening thinking tag. Two inference-time interventions—prefilling a single token and banning frequent opening tokens with in-context examples—successfully recover controllability, improving compliance by 34-41 percentage points. These interventions primarily enhance addition and style controllability, while suppression controllability shows varied responses. Performance correlates positively within these groups but negatively across groups, and monitorability depends on evaluation type.

Key points

• Chain-of-Thought monitoring fails because models collapse entropy in the first few tokens after the opening thinking tag.
• Prefilling a single token or banning frequent opening tokens with in-context examples recovers CoT controllability by 34-41 percentage points.

Context

This study investigates why current models struggle to control their verbal reasoning traces, linking the failure to an entropy collapse in initial tokens. The findings provide actionable interventions to improve CoT controllability, which is essential for effective agent oversight.

Limitations

Evidence is limited to a single arXiv preprint; results may vary across models and evaluation types. Suppression controllability shows varied responses, and monitorability correlations depend on the specific evaluation context.

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