NeuroWise: A Multi-Agent LLM "Glass-Box" System for Practicing Double-Empathy Communication with Autistic Partners

Albert Tang, Yifan Mo, Jie Li, Yue Su, Mengyuan Zhang +3 more
2/21/2026
cs.HCcs.AIcs.CY

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Abstract

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.

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Cite this paper

@article{tang2026neurowise,
  title  = {NeuroWise: A Multi-Agent LLM "Glass-Box" System for Practicing Double-Empathy Communication with Autistic Partners},
  author = {Albert Tang and Yifan Mo and Jie Li and Yue Su and Mengyuan Zhang and Sander L. Koole and Koen Hindriks and Jiahuan Pei},
  year   = {2026},
  eprint = {2602.18962},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2602.18962v1}
}

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