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LLM output layers reportedly destroy 95–99% of training signal during backpropagation
A post introducing the paper says the claimed loss significantly slows pretraining.
TLDR
A post sharing a paper titled “Lost in Backpropagation: The LM Head is a Gradient Bottleneck” claims that LLM output layers destroy 95–99% of training signal during backpropagation, significantly slowing pretraining.
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1 Source, first seen ago
