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cs.LG2026
A Scalable Measure of Loss Landscape Curvature for Analyzing the Training Dynamics of LLMs
Dayal Singh Kalra, Jean-Christophe Gagnon-Audet, Andrey Gromov +4
Understanding the curvature evolution of the loss landscape is fundamental to analyzing the training dynamics of neural networks. The most commonly studied measure, Hessian sharpne…
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…