arXiv (OAI Expanded)
open access
StackTok: Accelerating VLMs Inference with Budget-Adaptive Visual Token Selection
Increasing image resolution produces ever-longer visual-token sequences in vision-language models (VLMs), substantially raising their inference cost. To reduce this overhead without retraining, existing methods select compact token subsets that prioritize query relevance, visual coverage, or a fixed
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