系统梳理大模型核心原理，适合入门与参考。
Foundations of Large Language Models
- 分五大模块解析预训练、生成、提示、对齐与推理机制
- 聚焦基础理论而非前沿技术，内容结构清晰
- 适合NLP从业者及高校师生作为学习参考
本书是一部关于大语言模型的著作。正如书名所示，其重点在于基础概念，而非全面覆盖所有前沿技术。全书分为五个主要章节，分别探讨预训练、生成模型、提示工程、对齐机制和推理过程。内容面向自然语言处理及相关领域的高校学生、专业人员和实践者，可作为对大语言模型感兴趣的读者的参考手册。
原文摘要 · Abstract (English)
This is a book about large language models. As indicated by the title, it primarily focuses on foundational concepts rather than comprehensive coverage of all cutting-edge technologies. The book is structured into five main chapters, each exploring a key area: pre-training, generative models, prompting, alignment, and inference. It is intended for college students, professionals, and practitioners in natural language processing and related fields, and can serve as a reference for anyone interested in large language models.
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