GoKawiilResearchers propose 'Sleep' framework to curb catastrophic forgetting in LLMs
A new continual-learning method called the Sleep framework uses two stages—memory consolidation and dreaming—to help language models retain old knowledge while learning new tasks. Consolidation compresses short-term learning traces into model parameters using on-policy distillation and semantic rewards, while dreaming generates synthetic training examples by randomly activating different mixture-of-experts components and filtering them by gradient-based reward signals.