Not All Attention Heads Contribute to Critical Visual Token Selection: Head-Aware Pruning Matters More
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arXiv:2608.25332v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have exhibited impressive performance across diverse visual scenarios. However, this success comes at the cost of explosive growth in visual tokens, which imposes substantial memory and computational overhead during infer…
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- 2026-08-27 04:00 · arXiv cs.CV
Not All Attention Heads Contribute to Critical Visual Token Selection: Head-Aware Pruning Matters More