SOURCE-LINKED INTELLIGENCE

Multi-Image Visual Token Pruning in Large Visual Language Models

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

With the growing demand for processing multiple image sequences in real-world applications, various visual token pruning methods have emerged to mitigate the computational and context length constraints faced by Large Vision Language Models (LVLMs). However, most existing pruning approaches rely on static strategies that struggle to adapt across different architectural LVLMs and multi-image scenarios, and are additionally constrained by their dependence on attention computations that are incompatible with efficient techniques like FlashAttention. To address these limitations, we propose a trai

Read original source ↗ Open in workspace

recordType

paper

region

Global