3 articles tagged with #continual-learning.
A comparative analysis of approaches to catastrophic forgetting in language models, from parameter regularization to sparse memory architectures that reduce forgetting from 89% to just 11%.
Nested Learning: The Illusion of Deep Learning Architectures - A comprehensive guide to the arXiv paper revealing how neural networks learn at multiple timescales through hierarchical optimization.
Neural networks catastrophically forget previous knowledge when learning new tasks—not due to capacity limits but fundamental constraints in distributed learning systems.
