AINeutralarXiv – CS AI · 15h ago6/10
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What Makes Chain-of-Thought Work at Probe Time? Local Co-occurrence Rather Than Global Derivation
Researchers investigated why chain-of-thought prompting improves language model accuracy by analyzing what happens at inference time rather than generation time. They discovered that the improvement comes primarily from lexical activation and short-range token co-occurrence (2-3 adjacent tokens) rather than from logical sentence-level reasoning, challenging assumptions about how rationales actually drive model performance.