What Are Large Language Models Mapping to in the Brain? A Case Against Over-Reliance on Brain Scores

Understand

Given the remarkable capabilities of large language models (LLMs), there has been a growing interest in evaluating their similarity to the human brain.

• One approach towards quantifying this similarity is by measuring how well a model predicts neural signals, also called "brain score".
• Internal representations from LLMs achieve state-of-the-art brain scores, leading to speculation that they share computational principles with human language processing.
• This inference is only valid if the subset of neural activity predicted by LLMs reflects core elements of language processing.