activity
20242026
most citedCosmos World Foundation Model Platform for Physical AI

11 citations · 19 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2026★ 1 cited

DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos

Shenyuan Gao, William Liang, Kaiyuan Zheng +27

Being able to simulate the outcomes of actions in varied environments will revolutionize the development of generalist agents at scale. However, modeling these world dynamics, espe…

cs.AI2026

Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Moo Jin Kim, Yihuai Gao, Tsung-Yi Lin +8

Recent video generation models demonstrate remarkable ability to capture complex physical interactions and scene evolution over time. To leverage their spatiotemporal priors, robot…

cs.CV2026

Plenoptic Video Generation

Xiao Fu, Shitao Tang, Min Shi +5

Camera-controlled generative video re-rendering methods, such as ReCamMaster, have achieved remarkable progress. However, despite their success in single-view setting, these works…

cs.RO2026

Openpi Comet: Competition Solution For 2025 BEHAVIOR Challenge

Junjie Bai, Yu-Wei Chao, Qizhi Chen +13

The 2025 BEHAVIOR Challenge is designed to rigorously track progress toward solving long-horizon tasks by physical agents in simulated environments. BEHAVIOR-1K focuses on everyday…

cs.RO2025

Scalable Policy Evaluation with Video World Models

Wei-Cheng Tseng, Jinwei Gu, Qinsheng Zhang +4

Training generalist policies for robotic manipulation has shown great promise, as they enable language-conditioned, multi-task behaviors across diverse scenarios. However, evaluati…

cs.CV2025

World Simulation with Video Foundation Models for Physical AI

NVIDIA, :, Arslan Ali +87

We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2…

cs.CV2025

ArtiScene: Language-Driven Artistic 3D Scene Generation Through Image Intermediary

Zeqi Gu, Yin Cui, Zhaoshuo Li +6

Designing 3D scenes is traditionally a challenging task that demands both artistic expertise and proficiency with complex software. Recent advances in text-to-3D generation have gr…

cs.CV2025★ 2 cited

Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control

NVIDIA, :, Hassan Abu Alhaija +38

We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmen…

cs.AI2025★ 1 cited

Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning

NVIDIA, :, Alisson Azzolini +51

Physical AI systems need to perceive, understand, and perform complex actions in the physical world. In this paper, we present the Cosmos-Reason1 models that can understand the phy…

cs.CV2025★ 11 cited

Cosmos World Foundation Model Platform for Physical AI

NVIDIA, :, Niket Agarwal +76

Physical AI needs to be trained digitally first. It needs a digital twin of itself, the policy model, and a digital twin of the world, the world model. In this paper, we present th…

cs.CV2024★ 4 cited

Matting by Generation

Zhixiang Wang, Baiang Li, Jian Wang +4

This paper introduces an innovative approach for image matting that redefines the traditional regression-based task as a generative modeling challenge. Our method harnesses the cap…