Show and Tell: Prompt Strategies for Style Control in Multi-Turn LLM Code Generation

This article, sourced from ArXiv, focuses on prompt strategies for controlling the style of code generated by multi-turn Large Language Models (LLMs). The research likely explores different prompting techniques to influence the output's characteristics, such as coding style, readability, and adherence to specific conventions. The multi-turn aspect suggests an investigation into how these strategies evolve and adapt across multiple interactions with the LLM. The focus on style control is crucial for practical applications of LLMs in code generation, as it directly impacts the usability and maintainability of the generated code.