Introducing the Sleep Framework for Continual Learning in Large Language Models

The Sleep framework introduces a method for Large Language Models (LLMs) to retain knowledge during continual learning by simulating sleep phases. This approach mitigates catastrophic forgetting, enabling models to learn new tasks without losing previously acquired information.

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