AI RESEARCH
DAPE: Dynamic Non-uniform Alignment and Progressive Detail Enhancement Techniques for Improving the Performance of Efficient Visual Language Models
arXiv CS.AI
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ArXi:2605.08902v1 Announce Type: cross In recent years, pre-trained visual-linguistic models have nstrated tremendous potential, becoming a crucial foundational framework for numerous downstream tasks. However, the information density between text and images is not uniformly distributed. Existing methods often overlook the inherent and dynamic differences in information density and semantic scope between text