Stage 1): question clustering: partition questions of a given dataset into a few clusters
Stage 2): demonstration sampling: select a representative question from each cluster and generate its reasoning chain using Zero-Shot-CoT with simple heuristics
The simple heuristics could be length of questions (e.g., 60 tokens) and number of steps in rationale (e.g., 5 reasoning steps). This encourages the model to use simple and accurate demonstrations.
The process is illustrated below:
AUTOCOT
Image Source: Zhang et al. (2022)
Code for Auto-CoT is available here.https://www.promptingguide.ai/techniques/cot
Stage 2): demonstration sampling: select a representative question from each cluster and generate its reasoning chain using Zero-Shot-CoT with simple heuristics
The simple heuristics could be length of questions (e.g., 60 tokens) and number of steps in rationale (e.g., 5 reasoning steps). This encourages the model to use simple and accurate demonstrations.
The process is illustrated below:
AUTOCOT
Image Source: Zhang et al. (2022)
Code for Auto-CoT is available here.https://www.promptingguide.ai/techniques/cot