arxiv8h ago

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication

arXiv:2605.11165v4 Announce Type: replace Abstract: Federated learning (FL) in heterogeneous environments remains challenging because client models often differ in both architecture and data distribution. While recent approaches attempt to address this challenge through client clustering and knowled

arxivJun 25

Cosmos 3: Omnimodal World Models for Physical AI

arXiv:2606.02800v4 Announce Type: replace-cross Abstract: 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-transformers architecture. By supporting highly flexible input-

arxivMay 13

MCP-Cosmos: World Model-Augmented Agents for Complex Task Execution in MCP Environments

arXiv:2605.09131v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has unified the interface between Large Language Models (LLMs) and external tools, yet a fundamental gap remains in how agents conceptualize the environments within which they operate. Current paradigms are bifurcated:

Cosmos-H-Dreams news

NVIDIA Cosmos-H-Dreams: Bringing Real-Time Generative Simulation to Surgical Robotics

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication

Introducing Cosmos 3 Edge

Cosmos 3: Omnimodal World Models for Physical AI

Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action

Fine-Tuning NVIDIA Cosmos Predict 2.5 with LoRA/DoRA for Robot Video Generation

MCP-Cosmos: World Model-Augmented Agents for Complex Task Execution in MCP Environments

NVIDIA Cosmos Reason 2 Brings Advanced Reasoning To Physical AI