SPRIG: Improving Large Language Model Performance by System Prompt Optimization

Understand

Large Language Models (LLMs) have shown impressive capabilities in many scenarios, but their performance depends, in part, on the choice of prompt.

• Past research has focused on optimizing prompts specific to a task.
• However, much less attention has been given to optimizing the general instructions included in a prompt, known as a system prompt.
• To address this gap, we propose SPRIG, an edit-based genetic algorithm that iteratively constructs prompts from prespecified components to maximize the model's performance in general scenarios.