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Experts validate adaptability metrics for improving child-robot interaction and developmental appropriateness.
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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Rudenko et al. (2026) studied this question.
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