Reflective Prompt Tuning through Language Model Function-Calling

This paper proposes Reflective Prompt Tuning (RPT), a framework that uses large language model (LLM) function calling to simulate the iterative workflow of human prompt engineers. Its goal is to automate prompt optimization, reducing manual effort and overcoming limitations of existing methods that fail to capture systematic error patterns.