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Muon's advantage over Adam is rooted in a nuanced spectral profile that reveals underutilization of the loss landscape's bulk, leading to the development of a more efficient optimizer, SAMuon.
General-purpose self-supervised audio representations can outperform specialized supervised models, reshaping the landscape of audio understanding in ALLMs.
