  Chain-of-Thought (CoT), a step-wise and coherent reasoning chain, shows its
impressive strength when used as a prompting strategy for large language models
(LLM). Recent years, the prominent effect of CoT prompting has attracted
emerging research. However, there still lacks of a systematic summary about key
factors of CoT prompting and comprehensive guide for prompts utilizing. For a
deeper understanding about CoT prompting, we survey on a wide range of current
research, presenting a systematic and comprehensive analysis on several factors
that may influence the effect of CoT prompting, and introduce how to better
apply it in different applications under these discussions. We further analyze
the challenges and propose some future directions about CoT prompting. This
survey could provide an overall reference on related research.
