Large language model linguistic perplexity in childhood onset psychosis: unique features and developmental trends

Objective

Child and early adolescent onset psychosis (COP) is associated with subtle changes in language linked to thought disorder, a key contributor to functional impairment. Large language models (LLM) can detect deviations from expected language patterns by jointly analyzing sentence structure and word choice. This integrated information is captured by measures such as (pseudo)-perplexity, which quantify how difficult it is for an LLM to predict individual words given the surrounding linguistic context. The objective was to determine if perplexity measures change with age and whether they are altered in COP.