Semantic Structure of Feature Space in Large Language Models

This study demonstrates that the geometric relationships between semantic features in large language models' hidden states closely mirror human psychological associations. It shows that word vector projections onto semantic axes correlate with human ratings, and the similarity between these axes predicts the interconnections of semantic scales.