数据来源：ArXiv Domain LLM Domain Papers1. PLATE: Plasticity-Tunable Efficient Adapters for Geometry-Aware Continual LearningWe develop a continual learning method for pretrained models that \emph{requires no access to old-task data}, addressing a practical barrier in foundation model adaptation where pretraining distributions are often unavailable. Our key observation is that pretrained networks exhibit substantial \emph{geometric redundancy}, and that this redundancy can be exploited in two compl ...