On Meta-Prompting

Understand

Modern large language models (LLMs) are capable of interpreting input strings as instructions, or prompts, and carry out tasks based on them.

• Unlike traditional learners, LLMs cannot use back-propagation to obtain feedback, and condition their output in situ in a phenomenon known as in-context learning (ICL).
• Many approaches to prompting and pre-training these models involve the automated generation of these prompts, also known as meta-prompting, or prompting to obtain prompts.
• However, they do not formally describe the properties and behavior of the LLMs themselves.