Large Language Models in psycholinguistic studies

We are currently witnessing a veritable explosion of studies employing Large Language Models (LLMs) in the cognitive sciences. Here, we focus on their use in psycholinguistics, that is, for the study of human language processing. LLMs are primarily trained to predict upcoming or masked words in a given context. We briefly describe the transformer architecture which endows LLMs with impressive abilities to achieve this objectives, and review how the components of this architecture are of interest to psycholinguistics. We then review how LLMs are applied in research, focusing on (1) measuringsurprisal/probabilities of a word given a context; (2) extracting representations/embeddings these models produce, and (3) prompting/probing these models to produce an output, treating them similarly to human participants.