H-Probes: Extracting Hierarchical Structures From Latent Representations of Language Models

This paper introduces H-probes, linear probes designed to extract hierarchical structure, specifically depth and pairwise distance, from the latent representations of large language models. The research shows these probes robustly find low-dimensional subspaces crucial for performance in synthetic tree traversal tasks, generalizing well both within and out-of-domain.