Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for
Few-Shot Class-Incremental Learning
Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for
Few-Shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL) confronts the challenge of integrating new classes into a model with minimal training samples while preserving the knowledge of previously learned classes. Traditional methods widely adopt static adaptation relying on a fixed parameter space to learn from data that arrive sequentially, prone to overfitting to the …