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News/Rethinking the Harmonic Loss via Non-Euclidean Distance Layers
arxiv
PublishedApril 30, 2026 at 4:00 AM
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Rethinking the Harmonic Loss via Non-Euclidean Distance Layers

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arXiv:2603.10225v3 Announce Type: replace-cross Abstract: Cross-entropy loss has long been the standard choice for training deep neural networks, yet it suffers from interpretability limitations, unbounded weight growth, and inefficiencies that can contribute to costly training dynamics. The harmoni

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