AI RESEARCH
CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning
arXiv CS.LG
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ArXi:2604.14519v1 Announce Type: new Catastrophic forgetting remains a fundamental challenge in continual learning, in which models often forget previous knowledge when fine-tuned on a new task. This issue is especially pronounced in class incremental learning (CIL), which is the most challenging setting in continual learning. Existing methods to address catastrophic forgetting often sacrifice either model interpretability or accuracy. To address this challenge, we