arXiv Computation and Language
Aug 31

Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs

The paper introduces Semantic Head Specialization (SHS), a phenomenon where Vision Transformer (ViT) attention heads specialize as either object- or background-focused, most evident under full attention. It proposes the SHS-Index to quantify this specialization, demonstrating its ability to distinguish full-attention from chunk-window ViTs and its strong correlation with downstream benchmark performance. Leveraging insights into window interaction, token serialization, and local softmax allocation, the authors design Ariadne Attention, a hybrid attention mechanism that matches full-attention performance on 22 image and video tasks while reducing attention compute by 6.5×.

By Chenhong He, Lei Li, Shicheng Li, Hanglong Lv, Lingpeng Kong, Qi Liu, Tong Yang, Shuhuai Ren