标题： 生成式智能系统在群体情绪流动中的应用 显示英文标题

标题： Generative Intelligence Systems in the Flow of Group Emotions

摘要： 情感线索在交互环境中频繁出现并塑造群体动态，其中多个人类和人工代理通过共享的数字渠道进行交流。 虽然人工代理缺乏内在的情感状态，但它们可以使用文本或语音等合成模态来模拟情感行为。 这项工作引入了一个情绪传染协调模型，使代理能够检测情感信号，推断群体情绪模式，并生成有针对性的情感反应。 该系统捕捉人类的情感交流，并利用这些洞察力生成适应性、生成性反应，实时影响群体情感。 该模型通过将情感计算从个体层面的反应转向协调的群体层面情感调节，支持协作、教育和社会环境中的应用。 我们介绍了系统架构，并提供了实验结果，说明其在感知和引导群体情绪动态方面的有效性。 显示英文摘要

摘要： Emotional cues frequently arise and shape group dynamics in interactive settings where multiple humans and artificial agents communicate through shared digital channels. While artificial agents lack intrinsic emotional states, they can simulate affective behavior using synthetic modalities such as text or speech. This work introduces a model for orchestrating emotion contagion, enabling agents to detect emotional signals, infer group mood patterns, and generate targeted emotional responses. The system captures human emotional exchanges and uses this insight to produce adaptive, generative responses that influence group affect in real time. The model supports applications in collaborative, educational, and social environments by shifting affective computing from individual-level reactions to coordinated, group-level emotion modulation. We present the system architecture and provide experimental results that illustrate its effectiveness in sensing and steering group mood dynamics.