LLMs vs. the Brain: fMRI Evidence from Sentence-Level Analysis

TL;DR;

This study investigates the alignment between hierarchical representations in Large Language Models (LLMs) and human brain activity during natural language comprehension, finding that better model performance correlates with brain-like hierarchies and activity patterns. It uses fMRI data and hierarchical embeddings from 14 LLMs to predict brain signals, revealing that instruction tuning boosts LLM brain alignment.