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The paper identifies why deterministic few-step generation fails for text while succeeding for images: the sharp categorical readout in text decoders amplifies small errors, causing token flips, whereas continuous image decoders are smooth. It proposes diagnostics (DABI, CCI) and escape mechanisms such as categorical commitment and stochastic re-injection.