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Optimizing latent visual representations can boost multimodal reasoning performance by over 9% on complex tasks.
The proposed Attention-Guided Switching method allows MLLMs to dynamically balance between visual fidelity and logical coherence, achieving unprecedented efficiency in reasoning tasks.
