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cs.CV2026
LoC-Path: Learning to Compress for Pathology Multimodal Large Language Models
Qingqiao Hu, Weimin Lyu, Meilong Xu +5
Whole Slide Image (WSI) MLLMs are difficult to build and deploy because gigapixel slides induce thousands of visual tokens, while only a small fraction of regions is diagnostically…
cs.CV2026
Unrolled Networks are Conditional Probability Flows in MRI Reconstruction
Kehan Qi, Saumya Gupta, Xiaoling Hu +3
Unrolled networks have been widely used for Magnetic Resonance Imaging (MRI) reconstruction due to their efficiency. However, they typically exhibit unstable output quality across…
cs.CV2025
Efficient Whole Slide Pathology VQA via Token Compression
Weimin Lyu, Qingqiao Hu, Kehan Qi +4
Whole-slide images (WSIs) in pathology can reach up to 10,000 x 10,000 pixels, posing significant challenges for multimodal large language model (MLLM) due to long context length a…