Deep Learning
Pre-Norm
x = x + Sublayer(LN(x)) - normalisation inside the residual branch, leaving the residual stream unnormalised.
Why interviewers ask about it
Creates an uninterrupted identity path to layer 0, which removed the warmup fragility of the original post-norm transformer and enabled 100+ layer models.
Related terms
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