NeuroWise：一种多智能体大语言模型"玻璃箱"系统，用于与自闭症伙伴练习双 empathy 交流
NeuroWise: A Multi-Agent LLM "Glass-Box" System for Practicing Double-Empathy Communication with Autistic Partners
AI总结：
NeuroWise通过多智能体大语言模型帮助神经典型用户改善与自闭症伙伴的双 empathy 交流，减少缺陷归因并提高沟通效率。
摘要：
双 empathy 问题将神经多样性个体与神经典型个体之间的沟通困难归因于相互误解，但大多数干预措施却聚焦于自闭症个体。我们提出了NeuroWise，一种基于多智能体大语言模型的辅导系统，通过压力可视化、内部经验解读和情境指导来支持神经典型用户。在被试间研究（N=30）中，NeuroWise被所有参与者评为有帮助，并在基于缺陷的归因方面显示出显著的条件时间效应（p=0.02）：NeuroWise用户减少了缺陷归因，而基线用户在困难互动后倾向于归咎自闭症个体的缺陷。NeuroWise用户还更高效地完成了对话（37%更少的轮次，p=0.03）。这些发现表明，基于AI的解读可以通过帮助用户将沟通挑战视为相互来支持归因变化。
英文摘要：
The double empathy problem frames communication difficulties between neurodivergent and neurotypical individuals as arising from mutual misunderstanding, yet most interventions focus on autistic individuals. We present NeuroWise, a multi-agent LLM-based coaching system that supports neurotypical users through stress visualization, interpretation of internal experiences, and contextual guidance. In a between-subjects study (N=30), NeuroWise was rated as helpful by all participants and showed a significant condition-time effect on deficit-based attributions (p=0.02): NeuroWise users reduced deficit framing, while baseline users shifted toward blaming autistic "deficits" after difficult interactions. NeuroWise users also completed conversations more efficiently (37% fewer turns, p=0.03). These findings suggest that AI-based interpretation can support attributional change by helping users recognize communication challenges as mutual.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
