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MuonIO: Principled Norm-Aware Descent for Embedding Tables and Language Model Heads
The Muon optimizer derives its update rule for hidden linear layers by solving a local linearization of the loss penalized by the spectral norm, motivated by an RMS-stability argument for dense linear layers. Standard Muon implementations, however, exclude the input (embedding table) and output (lan
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