Long-form analogies generated by chatGPT lack human-like psycholinguistic properties

Understand

Psycholinguistic analyses provide a means of evaluating large language model (LLM) output and making systematic comparisons to human-generated text.

• These methods can be used to characterize the psycholinguistic properties of LLM output and illustrate areas where LLMs fall short in comparison to human-generated text.
• In this work, we apply psycholinguistic methods to evaluate individual sentences from long-form analogies about biochemical concepts.
• We compare analogies generated by human subjects enrolled in introductory biochemistry courses to analogies generated by chatGPT.