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    Muon training's claimed signature in model weights

    The post says Muon produces a distinctive spectral pattern compared with SGD or Adam, attributing it to more aggressive updates in low-magnitude directions.

    QG
    1 Source, 17d ago, first seen 17d ago

    TLDR

    One post argues that examining a model’s hidden-layer weights makes it easy to tell whether it was trained with Muon. It points to the spectral distribution—the spread of eigenvalues—of the matrix WᵀW as the telltale signature. The post says this pattern differs from SGD and Adam because Muon updates low-magnitude directions more aggressively.

    Combined views

    30

    1 Source, first seen 17d ago

    Combined views

    30

    1 Source, first seen 17d ago

    5 reposts
    5 reposts

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    1 Source

    @QuanquanGuRT @hayou_soufiane: It’s easy to tell whether Muon was used to train a model just by looking at the empirical spectral distribution of its…

    1 Source

    @QuanquanGuRT @hayou_soufiane: It’s easy to tell whether Muon was used to train a model just by looking at the empirical spectral distribution of its…