activity
20212025
most citedPrototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation

15 citations · 29 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2025

MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training

Yang Luo, Zangwei Zheng, Ziheng Qin +3

Large-batch training has become a cornerstone in accelerating the training of deep neural networks, yet it poses challenges in optimization and generalization. Existing optimizers…

cs.GR2025

Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Zangwei Zheng, Xiangyu Peng, Yuxuan Lou +30

Video generation models have achieved remarkable progress in the past year. The quality of AI video continues to improve, but at the cost of larger model size, increased data quant…

cs.CV202412 cited

Open-Sora: Democratizing Efficient Video Production for All

Zangwei Zheng, Xiangyu Peng, Tianji Yang +6

Vision and language are the two foundational senses for humans, and they build up our cognitive ability and intelligence. While significant breakthroughs have been made in AI langu…

cs.CV20212 cited

Multi-source Few-shot Domain Adaptation

Xiangyu Yue, Zangwei Zheng, Colorado Reed +3

Multi-source Domain Adaptation (MDA) aims to transfer predictive models from multiple, fully-labeled source domains to an unlabeled target domain. However, in many applications, re…

cs.CV2021

Scene-aware Learning Network for Radar Object Detection

Zangwei Zheng, Xiangyu Yue, Kurt Keutzer +1

Object detection is essential to safe autonomous or assisted driving. Previous works usually utilize RGB images or LiDAR point clouds to identify and localize multiple objects in s…

cs.CV202115 cited

Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation

Xiangyu Yue, Zangwei Zheng, Shanghang Zhang +4

Unsupervised Domain Adaptation (UDA) transfers predictive models from a fully-labeled source domain to an unlabeled target domain. In some applications, however, it is expensive ev…