Author

Mingyuan Zhang

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#machine learning Preprint Oct 2026

MASKerade: Token-Routed Mask Experts for Dense-to-MoE Upcycling

Sparsely activated Mixture-of-Experts (MoE) models increase model capacity without a proportional increase in per-token computation. Dense-to-MoE upcycling reuses pretrained dense models to construct such systems, commonly by copying feed-forward networks (FFNs) into independently trained experts. We introduce MASKerad...

Ming-Yuan Zhang, Yue Bai, Zhong-Ruo Wang et al. · 0 citations

Aug 2026

Random Sparse Networks Training with Sharpness-Aware Regularization.

This study examines a complementary perspective on LTH and proposes the Dual Lottery Ticket Hypothesis (DLTH), enabling general training for sparse networks and introduces Sharpness-Aware Random Sparse Network Transformation (SA-RST), which uses a regularization term to extrude information from weights slated for maski...

Yue Bai, Mingyuan Zhang, Huan Wang et al. · IEEE Transactions on Pattern... · 0 citations