A severe loss of previously learned performance when updating a shared representation on new material. Overlapping parameters allow transfer but also let a new objective change computations needed for older examples. Interleaving and representation design can reduce the problem; the mere presence of a neural network does not imply inevitable catastrophic forgetting.
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