Meta Prompting

Meta-prompting is a technique that uses large language models (LLMs) to generate or optimize prompts for other tasks, effectively creating a "prompting-of-prompting" system. Current research focuses on improving LLM performance in reasoning, understanding, and zero-shot learning by developing methods to automatically generate effective prompts, including those that decompose complex tasks into sub-tasks or leverage metacognitive strategies. This approach offers significant potential for enhancing LLM capabilities across diverse applications, ranging from improved question answering and visual recognition to more efficient and robust problem-solving.