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Cheap models can recover early evolutionary progress, enabling a shift in budget allocation that dramatically enhances LLM-driven algorithm discovery.
Turns out, MLLMs struggle with manufacturing tasks not because they can't "see," but because they lack the domain-specific knowledge to understand what they're looking at.
