PRewrite: Prompt Rewriting with Reinforcement Learning

“With the wide-scale proliferation of LLMs, prompting LLMs has become critical to achieving desired results on various downstream tasks. With the right prompts, LLMs can show impressive performance on various downstream tasks in zero-shot or few shot settings.

Currently, most prompt engineering is done on an ad-hoc basis and there are no clear universal guidelines on writing good prompts for various downstream tasks. This approach is prone to various problems. Writing good prompts is time-consuming and requires some amount of prior experience of working with LLMs to understand their performance and reasoning capabilities. It can also be ineffective as end-users who call the LLMs through APIs and even engineers might face difficulties in getting the LLMs to behave as intended through their hand-crafted prompts. Moreover, they might be sub-optimal as the manual prompts might not be optimized for the task at hand.”