Chain-of-thought prompting makes LLMs imitate exemplar formatting, concentrate their final answer probabilities, and activate a wider set of final-layer neurons.
Boosting of thoughts: Trial-and-error problem solving with large language models
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Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation
Chain-of-thought prompting makes LLMs imitate exemplar formatting, concentrate their final answer probabilities, and activate a wider set of final-layer neurons.