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20242026
most citedCosmos World Foundation Model Platform for Physical AI

11 citations · 30 across the 15 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

SAGE: Scalable Agentic 3D Scene Generation for Embodied AI

Hongchi Xia, Xuan Li, Zhaoshuo Li +9

Real-world data collection for embodied agents remains costly and unsafe, calling for scalable, realistic, and simulator-ready 3D environments. However, existing scene-generation s…

cs.CV2026

DuoGen: Towards General Purpose Interleaved Multimodal Generation

Min Shi, Xiaohui Zeng, Jiannan Huang +13

Interleaved multimodal generation enables capabilities beyond unimodal generation models, such as step-by-step instructional guides, visual planning, and generating visual drafts f…

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

Point-It-Out: Benchmarking Embodied Reasoning for Vision Language Models in Multi-Stage Visual Grounding

Haotian Xue, Yunhao Ge, Yu Zeng +4

Vision-Language Models (VLMs) have demonstrated impressive world knowledge across a wide range of tasks, making them promising candidates for embodied reasoning applications. Howev…

cs.CV2025

Efficient Part-level 3D Object Generation via Dual Volume Packing

Jiaxiang Tang, Ruijie Lu, Zhaoshuo Li +7

Recent progress in 3D object generation has greatly improved both the quality and efficiency. However, most existing methods generate a single mesh with all parts fused together, w…

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

Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation

Lu Ling, Chen-Hsuan Lin, Tsung-Yi Lin +7

Synthesizing interactive 3D scenes from text is essential for gaming, virtual reality, and embodied AI. However, existing methods face several challenges. Learning-based approaches…

cs.CV2025★ 1 cited

CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models

Qingqing Zhao, Yao Lu, Moo Jin Kim +12

Vision-language-action models (VLAs) have shown potential in leveraging pretrained vision-language models and diverse robot demonstrations for learning generalizable sensorimotor c…

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★ 3 cited

Edify 3D: Scalable High-Quality 3D Asset Generation

NVIDIA, :, Maciej Bala +22

We introduce Edify 3D, an advanced solution designed for high-quality 3D asset generation. Our method first synthesizes RGB and surface normal images of the described object at mul…

cs.CV2024★ 3 cited

EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generation

Jiaxiang Tang, Zhaoshuo Li, Zekun Hao +4

Current auto-regressive mesh generation methods suffer from issues such as incompleteness, insufficient detail, and poor generalization. In this paper, we propose an Auto-regressiv…

cs.CV2024★ 11 cited

SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes

Tianchang Shen, Zhaoshuo Li, Marc Law +5

Meshes are ubiquitous in visual computing and simulation, yet most existing machine learning techniques represent meshes only indirectly, e.g. as the level set of a scalar field or…