3 papers
cs.LG2026
A Faster Path to Continual Learning
Wei Li, Hangjie Yuan, Zixiang Zhao +3
Continual Learning (CL) aims to train neural networks on a dynamic stream of tasks without forgetting previously learned knowledge. Among optimization-based approaches, C-Flat has…
cs.LG2026
Continual GUI Agents
Ziwei Liu, Borui Kang, Hangjie Yuan +4
As digital environments (data distribution) are in flux, with new GUI data arriving over time-introducing new domains or resolutions-agents trained on static environments deteriora…
cs.LG2025
C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning
Wei Li, Hangjie Yuan, Zixiang Zhao +4
Balancing sensitivity to new tasks and stability for retaining past knowledge is crucial in continual learning (CL). Recently, sharpness-aware minimization has proven effective in…