AI RESEARCH
On the Invariance and Generality of Neural Scaling Laws
arXiv CS.LG
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ArXi:2605.07546v1 Announce Type: new Neural scaling laws establish a predictable relationship between model performance and data or compute, offering crucial guidance for resource allocation in new domains and tasks. Yet such laws are most needed precisely where they are hardest to obtain: fitting one for a new model task pair demands expensive sweeps that typically exhaust the very compute budget the law is meant to economize.