Prompt Selection

Prompt selection focuses on optimizing the input text given to large language models (LLMs) to maximize performance on downstream tasks. Current research emphasizes developing automated methods for selecting prompts, often employing metrics based on factors like emotional expression, logical consistency, complexity matching between prompts and test data, and mutual information between input and output. These advancements aim to improve the accuracy and efficiency of LLMs across diverse applications, from speech synthesis to text annotation and logical reasoning, ultimately reducing the reliance on manual prompt engineering.