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Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization

Wan, Weilin et al.
arXiv (All) · Papers
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machine-learning
Scaling laws govern macroscopic resource allocation for LLMs, yet precise architectural configurations for Mixture-of-Experts (MoE) models remain guided by heuristics. Existing MoE scaling studies either incorporate MoE-specific variables into scaling formulas, causing fitted coefficients to grow ra
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