1 citations · 1 across the 4 of their papers we have counts for
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Xray-Visual Models: Scaling Vision models on Industry Scale Data
Shlok Mishra, Tsung-Yu Lin, Linda Wang +24
We present Xray-Visual, a unified vision model architecture for large-scale image and video understanding trained on industry-scale social media data. Our model leverages over 15 b…
VGR: Visual Grounded Reasoning
Jiacong Wang, Zijian Kang, Haochen Wang +8
In the field of multimodal chain-of-thought (CoT) reasoning, existing approaches predominantly rely on reasoning on pure language space, which inherently suffers from language bias…
Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
Songtao Jiang, Yuan Wang, Sibo Song +22
Real-world clinical decision-making requires integrating heterogeneous data, including medical text, 2D images, 3D volumes, and videos, while existing AI systems fail to unify all…
DentVLM: A Multimodal Vision-Language Model for Comprehensive Dental Diagnosis and Enhanced Clinical Practice
Zijie Meng, Jin Hao, Xiwei Dai +20
Diagnosing and managing oral diseases necessitate advanced visual interpretation across diverse imaging modalities and integrated information synthesis. While current AI models exc…
Everything is a Video: Unifying Modalities through Next-Frame Prediction
G. Thomas Hudson, Dean Slack, Thomas Winterbottom +4
Multimodal learning, which involves integrating information from various modalities such as text, images, audio, and video, is pivotal for numerous complex tasks like visual questi…
Are Conditional Latent Diffusion Models Effective for Image Restoration?
Yunchen Yuan, Junyuan Xiao, Xinjie Li
Recent advancements in image restoration increasingly employ conditional latent diffusion models (CLDMs). While these models have demonstrated notable performance improvements in r…