Nitant Dube

Quantized Residuals to Continuous Prompts for Few-Shot Class Incremental Learning in Vision-Language Models

Few-shot Class-Incremental Learning (FSCIL) requires learning new classes from very limited data while preventing catastrophic forgetting. Existing methods rely mainly on visual features and are prone to overfitting, while recent vision-language models (VLMs) offer better transferability but suppres