DocuTeam：围绕演化文档的混合主动多智能体讨论
DocuTeam: Mixed-Initiative Multi-Agent Discussions around Evolving Documents
- KAIST（韩国科学技术院）
- Seoul National University（首尔国立大学）
- SkillBench
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
DocuTeam提出混合主动多智能体讨论系统，用户与智能体均可发起对话，智能体监控文档变化主动引导讨论，实验证明其提升结果新颖性、相关性和具体性且不增加认知负荷。
AI中文摘要：
在开放式问题解决中，协作者通常依赖讨论来揭示问题、挑战观点，并随着共享工作的演化而完善成果。虽然AI智能体越来越多地被用作讨论伙伴，但现有的多智能体系统给用户带来了沉重的负担，需要用户发起并精心编排讨论。我们提出了DocuTeam，一个混合主动的多智能体讨论系统，其中用户和智能体都可以发起和引导对话。智能体监控文档变化，以在工作演化时主动启动和重新定向讨论，而用户可以灵活地塑造对话或采纳智能体的想法。在一项受试者内研究（N=20）中，使用DocuTeam的参与者产生的结果在新颖性、相关性和具体性方面均显著高于基线，且认知负荷没有增加。与使用智能体进行一次性想法获取不同，参与者参与了一个迭代细化循环，其中文档变化促使智能体做出反应，进而引导用户重新审视并进一步发展他们的工作。
英文摘要：
In open-ended problem solving, collaborators often rely on discussion to surface concerns, challenge perspectives, and refine shared work as it evolves. While AI agents are increasingly used as discussion partners, existing multi-agent systems place a heavy burden on users to initiate and carefully orchestrate the discussions. We present DocuTeam, a mixed-initiative multi-agent discussion system in which both users and agents can initiate and steer conversations. Agents monitor document changes to proactively start and redirect discussions as the work evolves, while users can flexibly shape the conversation or adopt agent ideas. In a within-subjects study (N=20), participants using DocuTeam produced outcomes rated significantly more novel, relevant, and specific than with a baseline without any increase in cognitive load. Rather than using agents for one-off idea sourcing, participants engaged in an iterative refinement loop in which document changes prompted agent reactions, which led users to revisit and further develop their work.
