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LLMs learn skills in a surprisingly consistent order during pretraining, revealing a hidden curriculum that's predictable across models and readable from their internal representations.
Forget what you know: RAG's marginal utility hinges on model scale, task type, and pretraining saturation, offering a quantitative guide to balancing pretraining and retrieval.
