1 code implementation • 14 May 2024 • Zhimin Li, Jianwei Zhang, Qin Lin, Jiangfeng Xiong, Yanxin Long, Xinchi Deng, Yingfang Zhang, Xingchao Liu, Minbin Huang, Zedong Xiao, Dayou Chen, Jiajun He, Jiahao Li, Wenyue Li, Chen Zhang, Rongwei Quan, Jianxiang Lu, Jiabin Huang, Xiaoyan Yuan, Xiaoxiao Zheng, Yixuan Li, Jihong Zhang, Chao Zhang, Meng Chen, Jie Liu, Zheng Fang, Weiyan Wang, Jinbao Xue, Yangyu Tao, Jianchen Zhu, Kai Liu, Sihuan Lin, Yifu Sun, Yun Li, Dongdong Wang, Mingtao Chen, Zhichao Hu, Xiao Xiao, Yan Chen, Yuhong Liu, Wei Liu, Di Wang, Yong Yang, Jie Jiang, Qinglin Lu
For fine-grained language understanding, we train a Multimodal Large Language Model to refine the captions of the images.
no code implementations • 6 Mar 2023 • Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui
Recent years have witnessed the unprecedented achievements of large-scale pre-trained models, especially the Transformer models.
no code implementations • 16 Jun 2022 • Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui
First, to address the functionality of VFL models, we propose the federated source layers to unite the data from different parties.
1 code implementation • 9 Jun 2022 • Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui
Graph neural networks (GNNs) have achieved great success in many graph-based applications.
Ranked #11 on Node Property Prediction on ogbn-mag
1 code implementation • 1 Mar 2022 • Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui
Through deconstructing the message passing mechanism, PasCa presents a novel Scalable Graph Neural Architecture Paradigm (SGAP), together with a general architecture design space consisting of 150k different designs.
no code implementations • 26 Dec 2021 • Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao, Bin Cui
For example, the distributed K-core decomposition algorithm can scale to a large graph with 136 billion edges without losing correctness with our divide-and-conquer technique.
3 code implementations • 14 Dec 2021 • Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui
Embedding models have been an effective learning paradigm for high-dimensional data.
1 code implementation • NeurIPS 2021 • Wentao Zhang, Mingyu Yang, Zeang Sheng, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui
Recent works reveal that feature or label smoothing lies at the core of Graph Neural Networks (GNNs).
no code implementations • 23 Aug 2021 • Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui
Graph neural networks (GNNs) have recently achieved state-of-the-art performance in many graph-based applications.
no code implementations • 20 Apr 2021 • Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui
In recent studies, neural message passing has proved to be an effective way to design graph neural networks (GNNs), which have achieved state-of-the-art performance in many graph-based tasks.