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

Summary

A new paper links models' limited control over their chain-of-thought to an entropy collapse in the first few tokens after the opening thinking tag. Inference-time interventions on these initial tokens—prefilling or banning frequent opening tokens—improve average compliance by 34-41 percentage points and mainly recover addition and style controllability, while suppression controllability responds differently.

SourcearXiv AIAuthor: Hugh Van Deventer, Dmitrii Troitskii, Laura Ruis
The First Few Tokens Matter: Understanding Chain-of-Thought Controllability
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[Submitted on 29 Oct 2026]

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

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Abstract:Chain-of-thought (CoT) monitoring is a promising way to oversee increasingly capable agents. It succeeds in part because current models appear limited in their ability to control what they verbalize in their reasoning traces. We investigate the source of this limitation and link it to an entropy collapse in the first few tokens following the opening thinking tag. We exploit this mechanism to recover CoT controllability through two inference-time interventions on initial tokens: prefilling, where even a single token can substantially increase controllability, and banning frequent opening tokens combined with in-context examples, which improves average compliance by 34-41 percentage points across models. These interventions recover mainly addition and style controllability (adding or transforming information), while suppression controllability (avoiding or removing information) exhibits more varied responses, suggesting distinct underlying mechanisms. Consistent with this, the two groups behave as separate capabilities: across models, performance correlates positively within these groups, while cross-group correlations are mostly negative. Importantly, we find that the relationship with monitorability depends on the evaluation: addition and style controllability more consistently positively correlate with monitorability, while suppression often shows negative associations. Our findings motivate the development of controllability evaluations that distinguish difficulty initiating a specific opening from general limitations of the ability to alter reasoning content, alongside separate reporting of control tasks and categories.

Comments: 20 pages, 15 figures

Subjects:

Artificial Intelligence (cs.AI)

Cite as: arXiv:2610.40939 [cs.AI]

(or arXiv:2610.40939v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2610.40939

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Hugh Van Deventer V [view email] [v1] Thu, 29 Oct 2026 20:14:19 UTC (4,341 KB)

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Key points

  • Limited chain-of-thought controllability stems from entropy collapse in the first few tokens after the thinking tag.
  • Prefilling a single token or banning frequent opening tokens with in-context examples improves average compliance by 34-41 percentage points across models.
  • Interventions mainly recover addition and style controllability, while suppression controllability shows varied responses, suggesting distinct mechanisms.
  • Addition and style controllability positively correlate with monitorability, whereas suppression often shows negative associations.

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