Preprint Open access
Learning to Curate What You Generate for Generalizable Few-Shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL) aims to learn novel classes from limited annotations while preserving prior knowledge. Existing methods typically assume a sufficiently large base session, but this assumption fails when both base and incremental data are scarce, leading to weak initial representations, seman …