Tag: Vision-Language Models
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Are Vision-Language Models Ready to Aid Blind Users?
Explore how large vision-language models can support blind and low-vision individuals with improved accuracy and efficiency.
Blind Users’ Preferences for Vision-Language Scene Descriptions
Explore how blind and low-vision individuals prefer large vision-language model-generated scene descriptions to improve navigation and reduce anxiety.
Efficient CLIP Adaptation for Accurate Monocular Depth Estimation
Discover MoA-DepthCLIP, a lightweight framework using prompt-guided CLIP adaptation to improve monocular depth estimation with minimal supervision.
PixelPrune: Efficient Visual Token Reduction for VLMs
Discover PixelPrune, a pixel-level adaptive method that speeds up Vision-Language Models by reducing redundant visual tokens without losing accuracy.
CheXOne: AI Model for Chest X-ray Diagnosis & Reasoning
Discover CheXOne, an AI vision-language model that improves chest X-ray interpretation with diagnostic predictions and explicit clinical reasoning.