Problem
Research questions and friction points this paper is trying to address.
continual document authoring
knowledge integration
document revision
Knowledge Pull Requests for Continual Document Authoring
🤖 AI Summary
为持续文档编写引入知识拉取请求(KPRs)框架，通过提取、过滤和路由新知识到文档相应部分，并标记冲突，实现文档的可解释性更新。
📝 Abstract
We introduce Knowledge Pull Requests (KPRs), a framework for continual document authoring that makes each change interpretable. Documents require ongoing revision as new knowledge surfaces from other sources, languages, or times, but existing approaches either edit with no account of what knowledge changed or regenerate from scratch. A KPR integrates new knowledge into a document by extracting claims, filtering and routing them to sections, and flagging conflicts with existing content, producing a ChangeLog that separates what knowledge changes (claim proposal) from how the text changes (document diff). We evaluate KPRs on revising Wikipedia across languages and updating query-driven reports on RAGTIME. KPRs integrate more information and better preserve existing content than rewriting from sources or regenerating from scratch, while adding the most information per token generated. A KPR-revised article also grounds question answering better than a frontier model with search, which does not surface knowledge documented only in other languages.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Knowledge Pull Requests
continual document authoring
interpretable changes
ChangeLog
knowledge integration
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