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Zhejiang University, Zhejiang Key Laboratory of Digital-Intelligence Service Technology
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PriorTR reveals that ignoring model-induced priors can lead to the loss of critical task-specific information, enhancing MLLM efficiency without sacrificing accuracy.
Spectral analysis reveals that tokens with dynamic cross-layer evolution are crucial for preserving semantic integrity, leading to more efficient MLLMs.
