1 citations · 2 across the 5 of their papers we have counts for
5 papers
Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
Guannan Lai, Yujie Li, Xiangkun Wang +3
Class Incremental Learning (CIL) aims to enable models to learn new classes sequentially while retaining knowledge of previous ones. Although current methods have alleviated catast…
Exploring Open-world Continual Learning with Knowns-Unknowns Knowledge Transfer
Yujie Li, Guannan Lai, Xin Yang +3
Open-World Continual Learning (OWCL) is a challenging paradigm where models must incrementally learn new knowledge without forgetting while operating under an open-world assumption…
Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data
Yujie Li, Xiangkun Wang, Xin Yang +3
Open-world continual learning (OWCL) adapts to sequential tasks with open samples, learning knowledge incrementally while preventing forgetting. However, existing OWCL still requir…
Learning to Prompt Knowledge Transfer for Open-World Continual Learning
Yujie Li, Xin Yang, Hao Wang +2
This paper studies the problem of continual learning in an open-world scenario, referred to as Open-world Continual Learning (OwCL). OwCL is increasingly rising while it is highly…
Forgetting Prevention for Cross-regional Fraud Detection with Heterogeneous Trade Graph
Yujie Li, Yuxuan Yang, Xin Yang +2
With the booming growth of e-commerce, detecting financial fraud has become an urgent task to avoid transaction risks. Despite the successful applications of Graph Neural Networks…