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Homogeneous neural networks can be trained with provable generalization guarantees using significantly larger stepsizes than previously thought possible.
LLM benchmark accuracy jumps 10% when evaluated on a cleaned-up version of Humanity's Last Exam, highlighting the significant impact of dataset noise on performance metrics.
