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cs.CV2025
ERGO: Efficient High-Resolution Visual Understanding for Vision-Language Models
Jewon Lee, Wooksu Shin, Seungmin Yang +5
Efficient processing of high-resolution images is crucial for real-world vision-language applications. However, existing Large Vision-Language Models (LVLMs) incur substantial comp…
cs.CV2025
Efficient LLaMA-3.2-Vision by Trimming Cross-attended Visual Features
Jewon Lee, Ki-Ung Song, Seungmin Yang +6
Visual token reduction lowers inference costs caused by extensive image features in large vision-language models (LVLMs). Unlike relevant studies that prune tokens in self-attentio…
cs.CV2024
Layout-and-Retouch: A Dual-stage Framework for Improving Diversity in Personalized Image Generation
Kangyeol Kim, Wooseok Seo, Sehyun Nam +5
Personalized text-to-image (P-T2I) generation aims to create new, text-guided images featuring the personalized subject with a few reference images. However, balancing the trade-of…