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Residual connections solved vanishing gradients for transformers. But what if we revisited the problem with a different lens — pseudo-normalization offers a surprisingly simple alternative.

Self-attention scales as O(n²) with sequence length. As context windows push into the millions, this bottleneck is reshaping how we think about sequence modeling.