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cs.CV2026
CRISP: Pre-LLM Yet Text-Driven Visual Token Pruning for Efficient LVLM Inference
Xu Li, Yi Zheng, Mengyang Zhao +7
Large Vision-Language Models (LVLMs) typically require processing hundreds to thousands of visual tokens, leading to substantial inference overhead. Existing visual token pruning m…
cs.CV2025
Pyramid Token Pruning for High-Resolution Large Vision-Language Models via Region, Token, and Instruction-Guided Importance
Yuxuan Liang, Xu Li, Xiaolei Chen +4
Large Vision-Language Models (LVLMs) have recently demonstrated strong multimodal understanding, yet their fine-grained visual perception is often constrained by low input resoluti…
cs.CV2025
HERO: Rethinking Visual Token Early Dropping in High-Resolution Large Vision-Language Models
Xu Li, Yuxuan Liang, Xiaolei Chen +4
By cropping high-resolution images into local tiles and encoding them independently, High-Resolution Large Vision-Language Models (HR-LVLMs) have demonstrated remarkable fine-grain…