Resolution as a First-Class Decision: Task-Conditioned Routing for Efficient Multimodal Large Language Models

The inference efficiency of Multimodal Large Language Models (MLLMs) is severely constrained by massive visual token sequences induced by high-resolution inputs, with computational cost scaling quadratically. Existing approaches primarily focus on downstream token compression, while overlooking a fu