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Same Methods, Different Rankings: Trainable Depth as an Evaluation Variable in Continual Learning
Continual learning (CL) examines how models learn a sequence of tasks while retaining previously learned knowledge. Despite substantial progress in benchmarking CL methods, comparative evaluations typically keep the fine-tuning regime fixed. In this paper, we argue that the fine-tuning regime, defin
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