A More Word-like Image Tokenization for MLLMs

In three linesDiVT (Disentangled Visual Tokenization) clusters patch embeddings into coherent semantic units for MLLMs, creating discrete meaningful visual tokens instead of continuous streams. Adapts token budget to image complexity, reducing memory and latency while improving LLM compatibility.

Summary generated by Claude — human-verified