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cs.CV2026
DeepScan: A Training-Free Framework for Visually Grounded Reasoning in Large Vision-Language Models
Yangfu Li, Hongjian Zhan, Jiawei Chen +3
Humans can robustly localize visual evidence and provide grounded answers even in noisy environments by identifying critical cues and then relating them to the full context in a bo…
cs.CV2025
ShortV: Efficient Multimodal Large Language Models by Freezing Visual Tokens in Ineffective Layers
Qianhao Yuan, Qingyu Zhang, Yanjiang Liu +6
Multimodal Large Language Models (MLLMs) suffer from high computational costs due to their massive size and the large number of visual tokens. In this paper, we investigate layer-w…