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Independent Researcher
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LLMs struggle to capture true randomness, with no model surpassing 40% accuracy in sampling from target distributions, revealing a critical gap in their simulation capabilities.
Sequence recommendation models can achieve near-perfect scaling efficiency in distributed training, slashing wasted GPU cycles by up to 90%.
