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When Vision Becomes Text: Visual Token Pruning via Cross-Modal Residual Guidance in VLMs

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Abundant visual information strengthens vision-language model (VLM) perception, yet massive visual tokens raise inference costs. Existing visual token pruning methods rely on similarity-based guidance, which exploits pairwise text-vision and vision-vision token correlations for compression.

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