BID-LoRA: A Parameter-Efficient Framework for Continual Learning and Unlearning

ArXi:2604.12686v1 Announce Type: cross Recent advances in deep learning underscore the need for systems that can not only acquire new knowledge through Continual Learning (CL) but also remove outdated, sensitive, or private information through Machine Unlearning (MU). However, while CL methods are well-developed, MU techniques remain in early stages, creating a critical gap for unified frameworks that depend on both capabilities.