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Andrew Z. Wang

4 papers hereh-index 3240 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.AI1

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

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…

cs.CV2026

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

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation

Andrew Z. Wang, Songwei Ge, Tero Karras +2

Both text-to-image generation and large language models (LLMs) have made significant advancements. However, many text-to-image models still employ the somewhat outdated T5 and CLIP…

cs.AI2025

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…

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