Kavli Affiliate: Ke Wang | First 5 Authors: Yuwen Tan, Qinhao Zhou, Xiang Xiang, Ke Wang, Yuchuan Wu | Summary: Class-incremental learning (CIL) aims to enable models to continuously learn new classes while overcoming catastrophic forgetting. The introduction of pre-trained models has brought new tuning paradigms to CIL. In this paper, we revisit different parameter-efficient […]
Continue.. Semantically-Shifted Incremental Adapter-Tuning is A Continual ViTransformer