SOURCE-LINKED INTELLIGENCE
Doesn't Stop Reasoning: Analysis of Spurious CoT Termination
Chain-of-thought (CoT) reasoning improves large reasoning models (LRMs) on complex tasks but often produces long, redundant traces. Recent training-free early-exit methods shorten these traces by choosing an intermediate point to stop reasoning. We study one such strategy that injects an end-of-think token (EoT, ) at this point to trigger the reasoning-to-answering transition, and find that the injected EoT does not always induce a clean answering phase. Answering-phase generation can continue before the model regenerates another EoT, with the span preceding this regenerated EoT scaling with t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T10:25:23.000Z
First collected: 2026-09-21T04:51:57.792Z. This is not the publication date.