Carson Cary

GS-MoE: Training-Free MoE Compression via Groupwise Subspace Sharing and Pruning

Mixture-of-Experts (MoE) models reduce computation through sparse activation, but storing their expert parameters remains a major memory bottleneck. We introduce GS-MoE, a training-free compression framework that addresses redundancy across and within experts through two compression axes: shared-subspace rank and exper...