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cs.LG2026
Layers Matter: Why Continual Learning Regularization Should Be Layer-Adaptive
Brian B. Moser, Ahmed Anwar, Tobias Christian Nauen +5
Continual learning regularizers like EWC fight forgetting by penalizing changes from previous-task parameters with per-parameter importance, typically diagonal Fisher values. Per-p…
cs.LG2025
CLoRA: Parameter-Efficient Continual Learning with Low-Rank Adaptation
Shishir Muralidhara, Didier Stricker, René Schuster
In the past, continual learning (CL) was mostly concerned with the problem of catastrophic forgetting in neural networks, that arises when incrementally learning a sequence of task…