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arXiv cs.AI ·
What Does Chain-of-Thought Contribute at Probe Time? Evidence for Local Co-Occurrence Activation
תקציר מקורי באנגליתarXiv:2605.26795v2 Announce Type: replace Abstract: Chain-of-thought (CoT) prompting enhances large language model performance, yet what drives these gains remains unclear. We study this question from a probe-time perspective: holding CoT rationales fixed, we test which textual properties matter for the final prediction. Across multiple datasets and model configurations, we find that randomizing the order of rationale sentences has little effect on accuracy, suggesting that the global order of reasoning steps is not the main source of the probe-time benefit. Moreover, even when the words in a rationale are randomly reordered, performance remains well above the no-rationale baseline, indicating that the rationale's words remain useful even without their original order. Restoring only short-
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