3 papers
cs.CV2026
Dual-Imbalance Continual Learning for Real-World Food Recognition
Xiaoyan Zhang, Jiangpeng He
Visual food recognition in real-world dietary logging scenarios naturally exhibits severe data imbalance, where a small number of food categories appear frequently while many other…
cs.CV2026
One Adapter for All: Towards Unified Representation in Step-Imbalanced Class-Incremental Learning
Xiaoyan Zhang, Jiangpeng He
Class-incremental learning (CIL) aims to acquire new classes over time while retaining prior knowledge, yet most setups and methods assume balanced task streams. In practice, the n…
cs.LG2025
From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained Hypergradients
Nicolas Michel, Maorong Wang, Jiangpeng He +1
Continual Learning (CL) aims to learn from a non-stationary data stream where the underlying distribution changes over time. While recent advances have produced efficient memory-fr…