1 citations · 1 across the 5 of their papers we have counts for
6 papers
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…
Towards Generalizable Robotic Manipulation in Dynamic Environments
Heng Fang, Shangru Li, Shuhan Wang +3
Vision-Language-Action (VLA) models excel in static manipulation but struggle in dynamic environments with moving targets. This performance gap primarily stems from a scarcity of d…
3D-Generalist: Self-Improving Vision-Language-Action Models for Crafting 3D Worlds
Fan-Yun Sun, Shengguang Wu, Christian Jacobsen +13
Despite large-scale pretraining endowing models with language and vision reasoning capabilities, improving their spatial reasoning capability remains challenging due to the lack of…
SpecEval: Evaluating Code Comprehension in Large Language Models via Program Specifications
Lezhi Ma, Shangqing Liu, Lei Bu +3
Large Language models have achieved impressive performance in automated software engineering. Extensive efforts have been made to evaluate the abilities of code LLMs in various asp…
The 7th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +17
The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems…
The 6th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +14
The 6th edition of the AI City Challenge specifically focuses on problems in two domains where there is tremendous unlocked potential at the intersection of computer vision and art…