1 code implementation • 28 Jun 2023 • Ling Yang, Jiayi Zheng, Heyuan Wang, Zhongyi Liu, Zhilin Huang, Shenda Hong, Wentao Zhang, Bin Cui
To remove class spurious feature caused by distribution shifts, we propose Individual Graph Information Bottleneck (I-GIB) which discards irrelevant information by minimizing the mutual information between the input graph and its embeddings.
no code implementations • 21 Jun 2022 • YuFei Wang, Jiayi Zheng, Can Xu, Xiubo Geng, Tao Shen, Chongyang Tao, Daxin Jiang
This paper focuses on the data augmentation for low-resource NLP tasks where the training set is limited.
no code implementations • 19 May 2022 • Jiayi Zheng, Ling Yang, Heyuan Wang, Cheng Yang, Yinghong Li, Xiaowei Hu, Shenda Hong
To adequately leverage neighbor proximity and high-order information, we design a novel spatial autoregressive paradigm.
no code implementations • 25 Nov 2020 • Yongquan Yang, Yiming Yang, Jie Chen, Jiayi Zheng, Zhongxi Zheng
Learning from noisy labels is an important concern in plenty of real-world scenarios.