CMU researchers argue in Language Models Need Sleep that models should periodically consolidate recent context into persistent fast weights before clearing the cache, with longer sleep yielding the largest gains on examples demanding deeper reasoning.
Alongside it: a benchmark that scores models on writing benchmarks other models cannot clear, and an agent framework that treats a natural-language skill document as trainable state. Sleep, self-test, study, repeat.