88 citations · 113 across the 6 of their papers we have counts for
6 papers
Transitive Vision-Language Prompt Learning for Domain Generalization
Liyuan Wang, Yan Jin, Zhen Chen +4
The vision-language pre-training has enabled deep models to make a huge step forward in generalizing across unseen domains. The recent learning method based on the vision-language…
Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation
HongWei Yan, Liyuan Wang, Kaisheng Ma +1
To accommodate real-world dynamics, artificial intelligence systems need to cope with sequentially arriving content in an online manner. Beyond regular Continual Learning (CL) atte…
Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation
Yilin Lyu, Liyuan Wang, Xingxing Zhang +4
Continual learning entails learning a sequence of tasks and balancing their knowledge appropriately. With limited access to old training samples, much of the current work in deep n…
Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality
Liyuan Wang, Jingyi Xie, Xingxing Zhang +3
Prompt-based continual learning is an emerging direction in leveraging pre-trained knowledge for downstream continual learning, and has almost reached the performance pinnacle unde…
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence
Liyuan Wang, Xingxing Zhang, Qian Li +4
Continual learning aims to empower artificial intelligence (AI) with strong adaptability to the real world. For this purpose, a desirable solution should properly balance memory st…
CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One
Liyuan Wang, Xingxing Zhang, Qian Li +2
Continual learning requires incremental compatibility with a sequence of tasks. However, the design of model architecture remains an open question: In general, learning all tasks w…