研究背景
Large language models (LLMs) are increasingly being explored as facilitators of group discussion and collaborative work, but the behavioral differences between LLM-generated and human facilitation remain insufficiently characterized.
研究方法
We compare human Project Manager facilitation turns from scenario-based collaborative design meetings with Llama 3.1 8B Instruct responses across 199 paired contexts from the AMI Meeting Corpus.
The analysis covers five confirmatory dimensions: contextual semantic distance, a lexical elaboration proxy, empathy-and-hedge lexical density, topic divergence, and phase-vocabulary alignment.
An exploratory directiveness measure failed domain validation and is not interpreted.
研究结果
The sampled human Project Manager turns were higher on contextual semantic distance (r = 0.644) and on empathy-and-hedge lexical density (r = 0.203). The second contrast is carried mainly by hedge terms, so we read it as lexical hedging rather than psychological empathy.
Llama-generated facilitation was higher on topic divergence (r = 0.703), the lexical elaboration proxy (r = 0.288; lengthconfounded), and instruction-conditioned phase-vocabulary alignment (r = 0.382). A secondary no-phase check left the Llama-higher phase contrast in place.
The system prompt still requested a facilitation move, so that check is not evidence of spontaneous phase awareness.
研究结论
These differences should not be interpreted as a ranking of facilitation quality.
The resulting behavioral profile provides a reference point for later comparisons of LLM facilitators, human facilitators, prompts, models, and collaborative settings.