Feiyang Ye

According to our database, Feiyang Ye authored at least 17 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

M-Sim: Multi-level Semantic Inference Model for Chinese short answer scoring in low-resource scenarios.

Peichao Lai, Feiyang Ye, Yanggeng Fu, Zhiwei Chen, Yingjie Wu, Yilei Wang

Comput. Speech Lang., March, 2024

A Fast Attention Network for Joint Intent Detection and Slot Filling on Edge Devices.

Liang Huang, Senjie Liang, Feiyang Ye, Nan Gao

IEEE Trans. Artif. Intell., February, 2024

CogNLG: Cognitive graph for KG-to-text generation.

Peichao Lai, Feiyang Ye, Yanggeng Fu, Zhiwei Chen, Yingjie Wu, Yilei Wang, Victor Chang

Expert Syst. J. Knowl. Eng., January, 2024

Task-Aware Low-Rank Adaptation of Segment Anything Model.

Xuehao Wang, Feiyang Ye, Yu Zhang

CoRR, 2024

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization.

Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang

CoRR, 2024

2023

Decomposed Two-Stage Prompt Learning for Few-Shot Named Entity Recognition.

Feiyang Ye, Liang Huang, Senjie Liang, Kaikai Chi

Inf., May, 2023

A Unified Framework for Unsupervised Domain Adaptation based on Instance Weighting.

Jinjing Zhu, Feiyang Ye, Qiao Xiao, Pengxin Guo, Yu Zhang, Qiang Yang

CoRR, 2023

FedLPA: Personalized One-shot Federated Learning with Layer-Wise Posterior Aggregation.

Xiang Liu, Liangxi Liu, Feiyang Ye, Yunheng Shen, Xia Li, Linshan Jiang, Jialin Li

CoRR, 2023

A Scale-Invariant Task Balancing Approach for Multi-Task Learning.

Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu

CoRR, 2023

Partially-Labeled Domain Generalization via Multi-Dimensional Domain Adaptation.

Feiyang Ye, Jianghan Bao, Yu Zhang

Proceedings of the International Joint Conference on Neural Networks, 2023

Multi-Task Learning via Time-Aware Neural ODE.

Feiyang Ye, Xuehao Wang, Yu Zhang, Ivor W. Tsang

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning.

Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor W. Tsang

Trans. Mach. Learn. Res., 2022

Chinese Medical Named Entity Recognition Using External Knowledge.

Lin Zhang, Peichao Lai, Feiyang Ye, Ruixiong Fang, Ruiqing Wang, Jiayong Li, Yilei Wang

Proceedings of the PRICAI 2022: Trends in Artificial Intelligence, 2022

PCBERT: Parent and Child BERT for Chinese Few-shot NER.

Peichao Lai, Feiyang Ye, Lin Zhang, Zhiwei Chen, Yanggeng Fu, Yingjie Wu, Yilei Wang

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

A Closer Look at Loss Weighting in Multi-Task Learning.

Baijiong Lin, Feiyang Ye, Yu Zhang

CoRR, 2021

Safe Multi-Task Learning.

Pengxin Guo, Feiyang Ye, Yu Zhang

CoRR, 2021

Multi-Objective Meta Learning.

Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021