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cs.CV2026
ReViCo: Unveiling the Limitations of VLMs in Visual Text Understanding via Error Correction
Bojun Zhang, Junhong Liang, Feifei Zhai +2
Vision Language Models (VLMs) have shown great success in general visual tasks, yet they still struggle to deeply understand text within images. In this paper, we introduce ReViCo…
cs.CV2025
CROP: Contextual Region-Oriented Visual Token Pruning
Jiawei Guo, Feifei Zhai, Pu Jian +2
Current VLM-based VQA methods often process entire images, leading to excessive visual tokens that include redundant information irrelevant to the posed question. This abundance of…