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Adam's performance can be dramatically improved with a new memory-efficient variant that retains its advantages while cutting memory usage by 50%.
Polynomial preconditioning can significantly enhance LLM training stability and performance without adding inference overhead.
Adam's notorious divergence problem? Solved (with the right hyperparameter tuning).
