specific method · filed under optimization
Muon Split
A Muon variant that allows projection weights for different attention heads to update at different scales.
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Evidence
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The method, denoted as Muon Split, enables projection weights for different attention heads to update at different scales.
usedoptimizationin GLM-5Z.ai
Filed alongside
Other methods under optimization :: optimizer.
MuonPer-Head MuonAdamWCategory-specific assignment of Muon and AdamWSplit fused gradients before orthogonalizationNesterov momentumSinkhorn-balanced updateAdam without weight decay for the N-gram embedding tableAdamW for attention and GDN output gatesAdamW for gated-residual low-rank projectionsAdamW for input embeddings and output headAdamW for the MoE routerAsynchronous Micro-Group pipelineCanzonaCUDA graph capture of the optimizer stepEight-step Newton–Schulz iterationHybrid Muon and AdamW parameter-group optimizer assignmentHybrid Newton–Schulz iterationsHybrid optimization with Muon and AdamMoonlight-style learning-rate scalingMuon orthogonalization accuracy refinementMuon restricted to two-dimensional linear-map weightsMuownPeer-to-peer shard retrieval for Muon orthogonalization