Can Generic LLMs Help Analyze Child-adult Interactions Involving Children with Autism in Clinical Observation?

Understand

Large Language Models (LLMs) have shown significant potential in understanding human communication and interaction.

• However, their performance in the domain of child-inclusive interactions, including in clinical settings, remains less explored.
• In this work, we evaluate generic LLMs' ability to analyze child-adult dyadic interactions in a clinically relevant context involving children with ASD.
• Specifically, we explore LLMs in performing four tasks: classifying child-adult utterances, predicting engaged activities, recognizing language skills and understanding traits that are clinically relevant.