Splitting the vision encoder of an MLLM into domain-specific experts with a lightweight router yields small benchmark improvements at near-zero extra inference cost.
Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks
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Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts
Splitting the vision encoder of an MLLM into domain-specific experts with a lightweight router yields small benchmark improvements at near-zero extra inference cost.