Academic writing is an indispensable yet laborious part of the research enterprise. This Perspective maps out principles and methods for using generative artificial intelligence (AI), specifically large language models (LLMs), to elevate the quality and efficiency of academic writing. We introduce a human-AI collaborative framework that delineates the rationale (why), process (how), and nature (what) of AI engagement in writing. The framework pinpoints both short-term and long-term reasons for engagement and their underlying mechanisms (e.g., cognitive offloading and imaginative stimulation). It reveals the role of AI throughout the writing process, conceptualized through a two-stage model for human-AI collaborative writing, and the nature of AI assistance in writing, represented through a model of writing-assistance types and levels. Building on this framework, we describe effective prompting techniques for incorporating AI into the writing routine (outlining, drafting, and editing) as well as strategies for maintaining rigorous scholarship, adhering to varied journal policies, and avoiding overreliance on AI. Ultimately, the prudent integration of AI into academic writing can ease the communication burden, empower authors, accelerate discovery, and promote diversity in science.

翻译：学术写作是研究工作中不可或缺但费时费力的环节。本综述系统梳理了利用生成式人工智能（特指大语言模型）提升学术写作质量与效率的原理与方法。我们提出了一种人机协作框架，从AI参与的动因（为何）、过程（如何）及本质（是什么）三个维度进行阐述。该框架明确了短期与长期参与动机及其潜在机制（如认知卸载与想象激发），揭示了AI在写作全过程中的作用（通过人机协作写作的两阶段模型呈现），并展示了AI辅助写作的类型与层次模型。基于该框架，我们详细介绍了将AI融入写作流程（提纲拟定、初稿撰写与修改）的有效提示技巧，以及维持严谨学术规范、遵循多样化期刊政策、避免过度依赖AI的策略。最终，审慎整合AI于学术写作中，将减轻沟通负担、赋能研究者、加速科学发现并促进学术多样性。