StructLens: A Structural Lens for Language Models via Maximum Spanning Trees

Researchers introduced StructLens, a new analytical framework that uses maximum spanning trees to reveal global structural relationships between layers in language models, going beyond existing local token analysis methods. The approach shows different similarity patterns compared to traditional cosine similarity and proves effective for practical applications like layer pruning.