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The researchers re-examined five methods that had previously reported orthogonality improvements in pretraining and fine-tuning, and found that the reported gains could all be attributed to numerical precision, training duration, optimizer implementation, or per-row norm control, rather than orthogonality itself.
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11/3/2026
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