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Learning to GUIDE the Group: Self-Learning LLM Facilitation Across Multi-Party Tasks

L5 · ResearcherResearcharXiv· 10/12/2026

Presents novel self-learning methodology for multi-agent coordination with empirical validation of improved efficiency and social dynamics.

AI Summary

Researchers introduce GUIDE, a framework where LLMs learn generalized facilitation strategies from human conversations that outperform task-specific expert facilitators across diverse group settings.

Excerpt

As large language models are increasingly adopted as multi-party communication facilitators, there is a growing demand for agents capable of balancing diverse group dynamics across contexts. However, existing LLM facilitators are often fine-tuned for task-specific objectives; generalized LLM-based facilitation methods that can adapt to different types of tasks and diverse group dynamics are underdeveloped. To address this gap, we present GUIDE (Generalized Unified Intervention for Dynamic Exchan

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