Built with and by Teycir Ben Soltane•
How to Use•FAQ•GitHub•arXiv.org•
Share:
ArXivCSExplorer
☆☆Bookmarks🏆RSSHow to UseFAQ
Home/Authors/Zhangyang Wang

Zhangyang Wang

2 indexed papers

Recent (6 mo)
2
With code
0
Influential cites
0
Benchmarked
0

Publications per year

2
26

Top categories

Vision×1NLP×1AI×1ML×1

Frequent co-authors

Hezhen Hu1×
Wangbo Zhao1×
Lanqing Guo1×
Hanwen Jiang1×
Jonathan C. Liu1×
Zhiwen Fan1×

Research Timeline

2026
Not All Synthetic Data Is Yours to Learn From

Weak self-training on synthetic data can amplify a language model's existing capabilities, but this effect is strictly dependent on the compatibility between the source and student models, not on the data's intrinsic quality.

HumanNOVA: Photorealistic, Universal and Rapid 3D Human Avatar Modeling from a Single Image

HumanNOVA introduces a photorealistic, universal, and rapid model capable of generating high-quality 3D human avatars from a single input RGB image.

Highlighted terms show continued research focus across papers

Papers

cs.CVRecentJun 1, 2026

HumanNOVA: Photorealistic, Universal and Rapid 3D Human Avatar Modeling from a Single Image

Hezhen Hu, Wangbo Zhao, Lanqing Guo, Hanwen Jiang +5 more

HumanNOVA introduces a photorealistic, universal, and rapid model capable of generating high-quality 3D human avatars from a single input RGB image.

View →
cs.CLcs.AIcs.LGRecentMay 29, 2026

Not All Synthetic Data Is Yours to Learn From

Sina Alemohammad, Li Chen, Richard G. Baraniuk, Zhangyang Wang

Weak self-training on synthetic data can amplify a language model's existing capabilities, but this effect is strictly dependent on the compatibility between the source and student models, not on the…

View →