Source-grounded AI writing
Every AI step accountable to passages from your library—not empty chat.
基于文献的写作指 AI 辅助关联到你导入参考文献中的具体文字。在本地证据支持下，润色与续写已相对通用平台显出明显优势：更好的上下文契合、更紧的综述叙事、以及尊重你在文稿中所处位置的修订。
Key facts
- Flowing 是桌面写作应用——不是无论文库的浏览器聊天窗。
- 准备 → 写作 → 索文 → 带着上下文提问 → 润色 → 续写是核心闭环。
- 关键词索文将文稿术语匹配到已导入 PDF 中的片段。
- 上下文芯片将文稿或论文库片段附加到每次 AI 请求。
- 续写生成新话语；润色优化已有话语——二者不是同一任务。
- 润色针对话语功能（论证流、主张校准）——而非同义词替换。
What “grounded” means here
Grounding is not a marketing label—it is a constraint on what the model is allowed to treat as evidence. In Flowing, that evidence comes from your local PDF library and the passages you explicitly attach. The model may still err in interpretation, but it cannot cite a paper you never imported unless you paste it in yourself.
That is the difference from “empty chat,” where the model freely draws on parametric knowledge and may confabulate sources that sound right.
润色与续写背后的两条原则
续写生成新话语——例如在主张后引入代表性研究再综合。润色优化你已写的话语——组织证据、校准主张、修正范围漂移。带准确性审阅的深度润色更接近学术修订，而非「让它更好听」。
Flowing 遵循：优先改进段落的话语功能，而非改进措辞。成功的建议让论证更易跟随——而非仅仅更优雅。
The six-step workflow
Prepare by importing reference PDFs. Write in rich text or LaTeX with live preview. Recall surfaces relevant library passages for keywords in your draft. Ask with context for synthesis or clarification on attached passages. Polish rewrites paragraphs with basis-backed suggestions. Continue writing extends your thread with cited evidence—not boilerplate.
Each step keeps the manuscript and your sources in one workspace, so you spend less time switching between PDF reader, chat tab, and editor.
When to choose source-grounded writing
Choose this approach when the deliverable will be reviewed for accuracy—journal submissions, theses, grant proposals, and literature reviews. Skip it when you only need unstructured brainstorming with no citation obligations.
Flowing is optimized for the first case. See our literature review and fake citations guides for field-specific workflows.