1 code implementation • 6 May 2024 • Shuhao Mei, Yuxi Zhou, Jiahao Xu, Yuxuan Wan, Shan Cao, Qinghao Zhao, Shijia Geng, Junqing Xie, Shenda Hong
However, these methods fail to early predict an individual's probability of COPD in the future based on subtle features in the spirogram.
no code implementations • 26 Mar 2024 • Yilun Zheng, Jiahao Xu, Lihui Chen
Under circumstances of heterophily, where nodes with different labels tend to be connected based on semantic meanings, Graph Neural Networks (GNNs) often exhibit suboptimal performance.
Ranked #17 on Node Classification on Texas
1 code implementation • NAACL 2022 • Jiahao Xu, Yubin Ruan, Wei Bi, Guoping Huang, Shuming Shi, Lihui Chen, Lemao Liu
Back translation (BT) is one of the most significant technologies in NMT research fields.
1 code implementation • 20 Oct 2023 • Jiahao Xu, Wei Shao, Lihui Chen, Lemao Liu
This paper proposes the DistillCSE framework, which performs contrastive learning under the self-training paradigm with knowledge distillation.
1 code implementation • 15 Sep 2023 • Yancheng Cai, Bo Zhang, Baopu Li, Tao Chen, Hongliang Yan, Jingdong Zhang, Jiahao Xu
Therefore, we focus on cross-domain background feature alignment while minimizing the influence of foreground features on the cross-domain alignment stage.
no code implementations • 22 May 2023 • Jiahao Xu, Wei Shao, Lihui Chen, Lemao Liu
This paper improves contrastive learning for sentence embeddings from two perspectives: handling dropout noise and addressing feature corruption.
1 code implementation • CVPR 2023 • Divya Saxena, Jiannong Cao, Jiahao Xu, Tarun Kulshrestha
Re-GAN stabilizes the GANs models with less data and offers an alternative to the existing GANs tickets and progressive growing methods.
no code implementations • 20 May 2022 • Jiahao Xu, Zihuai Lin
Second, we investigate some deep learning models based on CNN (ResNet34, hierarchical structure) and other deep learning models (LSTM, CLDNN).
no code implementations • 28 Oct 2020 • Xiaoyu Kou, Yankai Lin, Yuntao Li, Jiahao Xu, Peng Li, Jie zhou, Yan Zhang
Knowledge graph embedding (KGE), aiming to embed entities and relations into low-dimensional vectors, has attracted wide attention recently.
1 code implementation • 23 Sep 2020 • Xinyi Zhang, Jiahao Xu, Charlie Soh, Lihui Chen
In this paper, we propose a Label-based Attention for Hierarchical Mutlti-label Text Classification Neural Network (LA-HCN), where the novel label-based attention module is designed to hierarchically extract important information from the text based on the labels from different hierarchy levels.
Multi Label Text Classification Multi-Label Text Classification +1