The sleep framework: A new way for LLMs to retain knowledge in continual learning

Researchers propose a sleep-inspired continual learning framework for large language models (LLMs) that alternates active interaction with offline memory consolidation, enabling LLMs to retain knowledge over long contexts and improve reasoning without catastrophic forgetting.