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cs.LG2026
Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate
Dayal Singh Kalra, Maissam Barkeshli
Hyperparameter transfer allows extrapolating optimal optimization hyperparameters from small to large scales, making it critical for training large language models (LLMs). This is…
cs.LG2026
On the origin of neural scaling laws: from random graphs to natural language
Maissam Barkeshli, Alberto Alfarano, Andrey Gromov
Scaling laws have played a major role in the modern AI revolution, providing practitioners predictive power over how the model performance will improve with increasing data, comput…