Google introduces 'Sleep' paradigm for continual learning in LLMs
Google researchers present a two‑stage 'Sleep' framework for large language models that distills short‑term in‑context knowledge into stable long‑term parameters via upward distillation and a reinforcement‑learning‑driven 'Dreaming' phase. Experiments show improved continual‑learning, knowledge incorporation, and few‑shot generalization.