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Research questionHow can an LLM delegate decide when to speak and which absent participant ideas to recover as meeting turns arrive?An online delegate must infer evolving stances, topic coverage, and conversational floor from each observed turn. Without this situational awareness, it may miss opportunities to represent the absent participant or surface an inappropriate contribution.
AI
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Multi-agent Systems
Natural Language Processing
Latest papersRecent research connected to this question, newest first.Speak for Me: Giving LLMs the Situational Awareness to Participate in a MeetingThe source evaluates CAPA, which maintains meeting state from each observed turn and makes online decisions about whether to speak and which proposition to surface. Evidence comes from 137 AMI meetings and an episode-level protocol scoring whether, when, and what the delegate contributes around actual idea units; its schema-constrained LLM judges align with human annotations at Cohen’s kappa = 0.71.research paper · Sep 3, 2026
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