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Paper

On the Optimizer Dependence of Neural Scaling Laws

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AI summary

arXiv:2605. 29387v1 Announce Type: cross Abstract: The scaling exponent $\alpha$ in neural scaling laws $L(N) \propto N^{-\alpha}$ is commonly treated as a fixed constant set by architecture and data.