University research labs often rely on chat-based platforms for communication and project management, where valuable knowledge surfaces but is easily lost in message streams. Documentation can preserve knowledge, but it requires ongoing maintenance and is challenging to navigate. Drawing on formative interviews that revealed organizational memory challenges in labs, we designed CHOIR, an LLM-based chatbot that supports organizational memory through four key functions: document-grounded Q\&A, Q\&A sharing for follow-up discussion, knowledge extraction from conversations, and AI-assisted document updates. We deployed CHOIR in four research labs for one month (n=21), where the lab members asked 107 questions and lab directors updated documents 38 times in the organizational memory. Our findings reveal a privacy-awareness tension: questions were asked privately, limiting directors' visibility into documentation gaps. Students often avoided contribution due to challenges in generalizing personal experiences into universal documentation. We contribute design implications for privacy-preserving awareness and supporting context-specific knowledge documentation.

翻译：大学研究实验室通常依赖基于聊天的平台进行沟通和项目管理，其中有价值的知识会浮现但容易在信息流中丢失。文档记录可以保存知识，但需要持续维护且难以有效检索。基于揭示实验室组织记忆挑战的形成性访谈，我们设计了CHOIR——一种基于大型语言模型的聊天机器人，通过四个核心功能支持组织记忆：基于文档的问答、用于后续讨论的问答共享、从对话中提取知识以及人工智能辅助的文档更新。我们在四个研究实验室部署CHOIR一个月（n=21），期间实验室成员提出了107个问题，实验室负责人在组织记忆中更新了38次文档。研究发现存在隐私意识与信息透明的矛盾：问题多以私密方式提出，限制了负责人对文档缺失的可见性。学生常因难以将个人经验泛化为通用文档而回避贡献。我们提出了保护隐私的感知机制和支持情境化知识记录的设计启示。