Prompt Engineering and Calibration for Zero-Shot Commonsense Reasoning
Chenkai Ma · arXiv (Cornell University) · 2023
Prompt engineering and calibration make large language models excel at reasoning tasks, including multiple choice commonsense reasoning. From a practical perspective, we investigate and evaluate these strategies on smaller language models. Through experiments on five commonsense reasoning benchmarks, we find that each strategy favors certain models, but their joint effects are mostly negative.