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Small models locked out of rare tasks; large models prioritize common tasks first

Small models don't just learn slower. They're structurally locked out of rare tasks forever. No matter how long you train them, frequent task signals constantly overwrite rare ones. Large models solve this by fully satisfying common tasks first, then dedicating leftover

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