This survey has provided a systematic overview of the emerging field of LLM-enabled compilation by addressing several key research questions. We first answered how LLMs are being integrated by proposing a comprehensive, multi-dimensional taxonomy that categorizes works based on their Design Philosophy (Selector, Translator, Generator), LLM Methodology, their operational Level of Code Abstraction, and the specific Task Type they address. In answering what advancements these approaches offer, we identified three primary benefits: the democratization of compiler development, the discovery of novel optimization strategies, and the broadening of the compiler's traditional scope. Finally, in addressing the field's challenges and opportunities, we highlighted the critical hurdles of ensuring correctness and achieving scalability, while identifying the development of hybrid systems as the most promising path forward. By providing these answers, this survey serves as a foundational roadmap for researchers and practitioners, charting the course for a new generation of LLM-powered, intelligent, adaptive and synergistic compilation tools.

翻译：本综述通过探讨若干关键研究问题，对LLM赋能编译这一新兴领域进行了系统性概述。我们首先通过提出一个多维分类框架来阐释LLM的集成方式，该框架依据设计理念（选择器、转换器、生成器）、LLM方法论、代码抽象层级以及所处理的具体任务类型对现有工作进行分类。在回答这些方法带来何种进展时，我们总结了三大核心优势：编译器开发的民主化、新型优化策略的发现以及编译器传统范畴的拓展。最后，针对该领域的挑战与机遇，我们重点指出了确保正确性与实现可扩展性这两大关键障碍，同时提出开发混合系统是最具前景的发展路径。通过回答这些问题，本综述为研究者和实践者提供了基础路线图，为新一代LLM驱动的智能、自适应、协同编译工具的发展指明了方向。