most citedMeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

8 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code

Jiaxiang Tang, Yi Zhou, Chad DeLuca +5

Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and without altering unrelated cont…

cs.NI2026

Multipath Adaptive Video Streaming with Multiple Description Neural Video Codec over 5G Networks

Xinyue Hu, Ziyan Wu, Jiaxiang Tang +5

5G networks employ multiple radio channels to meet growing demands for bandwidth and high-resolution video streaming for emerging applications. However, existing multipath video sy…

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.CV2024

Robust Multiple Description Neural Video Codec with Masked Transformer for Dynamic and Noisy Networks

Xinyue Hu, Wei Ye, Jiaxiang Tang +2

Multiple Description Coding (MDC) is a promising error-resilient source coding method that is particularly suitable for dynamic networks with multiple (yet noisy and unreliable) pa…

cs.CV2024★ 8 cited

MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Yiwen Chen, Tong He, Di Huang +9

Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement. However, this poten…