most citedFederated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

11 citations · 11 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2026

NV-Generate-Body: 3D Latent Diffusion Model forControllable Anatomy, Tumor, and Demographic Body Mask Synthesis

Can Zhao, Pengfei Guo, Dong Yang +8

Curating large labeled CT datasets is expensive and constrained by patient privacy. We present NV-Generate-BodyMask, a 3D latent diffusion model that synthesizes whole-body CT segm…

cs.CV2026

Token-Based Affordance Grounding with Large Vision-Language Models

Seung Il Lee, Qinqian Lei, Daguang Xu +4

Affordance grounding aims to localize image regions that support a specific action, serving as a core capability for physical intelligence and embodied perception. Previous studies…

cs.CV2026

Cosmos 3: Omnimodal World Models for Physical AI

NVIDIA, :, Aditi +293

We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…

cs.AI2026

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models

Junqi Liu, Selena Song, Yuhan Wang +12

Autonomous agents are increasingly expected to support end-to-end medical-AI research workflows, moving beyond isolated prediction tasks or short-form clinical question answering.…

cs.AI2026

Surg: A Spectrum of Large-Scale Multimodal Data and Foundation Models for Surgical Intelligence

Zhitao Zeng, Mengya Xu, Jian Jiang +13

Surgical intelligence has the potential to improve the safety and consistency of surgical care, yet most existing surgical AI frameworks remain task-specific and struggle to genera…

cs.CV2026

LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis

Zhifan Jiang, Dong Yang, Vishwesh Nath +7

Large vision-language models (VLMs) have evolved from general-purpose applications to specialized use cases such as in the clinical domain, demonstrating potential for decision sup…

eess.IV2020★ 11 cited

Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

Dong Yang, Ziyue Xu, Wenqi Li +17

The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able t…