C-LoRA: Continual Low-Rank Adaptation for Pre-trained Visual Models
C-LoRA addresses catastrophic forgetting in sequential tasks by using a single LoRA adapter to handle multiple tasks. It introduces a learnable routing matrix R that splits adaptation into a stability component (Rbase) for old knowledge and a plasticity component (Rδ) for new task adaptation. This mechanism controls how updates are applied, ensuring prior knowledge is preserved while allowing efficient learning of new tasks.