SOURCE-LINKED INTELLIGENCE

Toppling the Hierarchy in Byte-level Language Modeling

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

This work examines recent byte-level models and their failure to perfectly manipulate characters. State-of-the-art byte-level models use a hierarchical structure, starting at the byte level, downsampling to the word level, and then upsampling back to bytes. While this improves training and inference efficiency, we find that the hierarchical design itself limits character-level understanding, with pure byte-level models consistently outperforming hierarchical variants on character manipulation tasks. Ablating transformer layers into attention and feed-forward components further reveals that byt

Read original source ↗ Open in workspace

recordType

paper

region

Global