What question did this study set out to answer?

This research aims to define metrics to validate language models for child-robot conversation.

February 26, 2026Open Access

Towards a Child-Appropriate LLM for Child–Robot Conversation

Key Points

This research aims to define metrics to validate language models for child-robot conversation.
Gathered insights from experts in psychology, social robotics, and language models.
Developed metrics focusing on age and developmental appropriateness.
Identified key areas for validation of language models in child-robot interactions.
Proposed specific metrics to evaluate adaptability to children's needs.

Abstract

Large Language Models (LLMs) hold significant promise for enhancing Child–Robot Interaction (CRI), offering advanced conversational skills and adaptability to the diverse abilities, requests and needs of young children. Little attention, however, has been paid to evaluating the age and developmental appropriateness of LLMs. This paper brings together experts in psychology, social robotics and LLMs to define metrics for the validation of LLMs for child–robot interaction.

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