让专家与AI协作写学术专著，提升长文本一致性与引用准确性。
CoAuthorAI: A Human in the Loop System For Scientific Book Writing
- 结合检索增强生成与专家设计的层级大纲，实现结构化写作。
- 500章文献综述测试中标题召回率达98%，100篇人工评估满意度达82%。
- 适合需要高质量长篇科研写作的学者与出版机构使用。
大语言模型在科学写作中应用日益广泛，但在撰写专著类长文本时仍存在结构不一致、引文不可靠等问题。我们提出CoAuthorAI，一种人机协同的写作系统，融合检索增强生成、专家设计的分层大纲与自动参考链接功能。该系统支持专家在句子层面持续迭代修改，保障内容连贯性与准确性。在500个跨领域文献综述章节的评估中，最大软标题召回率达到98%；对100篇文章的人工评估显示，生成内容满意度达82%。基于CoAuthorAI与科信科技LUFFA AI模型合作撰写的《岩石动力学》专著已由Springer Nature出版。结果表明，系统性的人机协作可将大模型能力从论文扩展至整本专著，推动更高效可靠的科学出版。
原文摘要 · Abstract (English)
Large language models (LLMs) are increasingly used in scientific writing but struggle with book-length tasks, often producing inconsistent structure and unreliable citations. We introduce CoAuthorAI, a human-in-the-loop writing system that combines retrieval-augmented generation, expert-designed hierarchical outlines, and automatic reference linking. The system allows experts to iteratively refine text at the sentence level, ensuring coherence and accuracy. In evaluations of 500 multi-domain literature review chapters, CoAuthorAI achieved a maximum soft-heading recall of 98%; in a human evaluation of 100 articles, the generated content reached a satisfaction rate of 82%. The book AI for Rock Dynamics generated with CoAuthorAI and Kexin Technology's LUFFA AI model has been published with Springer Nature. These results show that systematic human-AI collaboration can extend LLMs' capabilities from articles to full-length books, enabling faster and more reliable scientific publishing.
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