Adding zeroth- and first-order flatness penalties to continual learning losses yields small consistent accuracy gains across seven methods, with the gated C-Flat++ variant at roughly 30% of the update cost.
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C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning
Adding zeroth- and first-order flatness penalties to continual learning losses yields small consistent accuracy gains across seven methods, with the gated C-Flat++ variant at roughly 30% of the update cost.