Catastrophic Forgetting

A phenomenon where neural networks lose previously learned knowledge when trained on new data. Catastrophic forgetting is a major challenge in continual learning scenarios where models need to adapt to new tasks without losing competence on earlier ones. Techniques like elastic weight consolidation address this problem.