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Redundancy Meets Synergy: Dependency-aware Expert Selection for MoE via Submodular Optimization
While Mixture-of-Experts (MoE) models effectively scale model capacity through sparse activation, their deployment is often bottlenecked by prohibitive memory requirements. Extracting a compact subset of experts presents a promising solution. However, existing expert selection heuristics predominant
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