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cs.CV2026
VANTAGE-Bench: Evaluating the Infrastructure AI Gap in Vision-Language Models
Zaid Pervaiz Bhat, Nimra Nayyar, Arihant Jain +6
As Vision-Language Models (VLMs) advance toward physical deployment, the focus has remained on action-oriented Embodied AI evaluated on subject-centric consumer video. This overloo…
cs.CV2026
From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning
Han Zhang, Yilin Zhao, Zaid Pervaiz Bhat +5
Detecting a traffic anomaly does not establish whether a video-language model can explain what happened, localize it in time, or identify its causes. We introduce TAR (Traffic Anom…
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…