The concept is simple. For a model with $N$ layers, I define a configuration $(i, j)$. The model processes layers $0$ to $j{-}1$ as normal, then loops back and reuses layers $i$ through $j{-}1$ again, and then the rest to $N{-}1$. The layers between $i$ and $j{-}1$ get duplicated in the execution path. No weights are changed. The model just traverses some of its own layers twice.
18:22, 27 февраля 2026Ценности,更多细节参见PDF资料
https://16colo.rs/pack/blocktronics-space/。新收录的资料对此有专业解读
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