用大模型实时生成对话图谱，让线上会议思路更清晰
MeetMap: Real-Time Collaborative Dialogue Mapping with LLMs in Online Meetings
- 用大模型将会议内容转为可交互的对话图谱
- 用户对两种模式均更满意，尤其偏好低负担的AI-Map
- 适合需要快速理清会议逻辑的团队协作场景
视频会议平台通常以线性文字记录对话，但会议中的思想发展并非线性。本文利用大语言模型实时生成对话图谱，帮助与会者直观梳理和关联观点。设计了两种系统变体：Human-Map中，AI生成对话摘要作为节点，由用户构建图谱；AI-Map中，AI直接生成图谱，用户可编辑。通过10对用户的交叉实验对比，发现用户更倾向使用MeetMap进行笔记，其结构更契合思维模型。用户认为AI-Map操作简便、负担轻；Human-Map则提供了更强的主动理解机会。
原文摘要 · Abstract (English)
Video meeting platforms display conversations linearly through transcripts or summaries. However, ideas during a meeting do not emerge linearly. We leverage LLMs to create dialogue maps in real time to help people visually structure and connect ideas. Balancing the need to reduce the cognitive load on users during the conversation while giving them sufficient control when using AI, we explore two system variants that encompass different levels of AI assistance. In Human-Map, AI generates summaries of conversations as nodes, and users create dialogue maps with the nodes. In AI-Map, AI produces dialogue maps where users can make edits. We ran a within-subject experiment with ten pairs of users, comparing the two MeetMap variants and a baseline. Users preferred MeetMap over traditional methods for taking notes, which aligned better with their mental models of conversations. Users liked the ease of use for AI-Map due to the low effort demands and appreciated the hands-on opportunity in Human-Map for sense-making.
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