Humanizing longer pieces: where quality falls apart and why

humanizing longer pieces seems to be where every tool falls apart. works fine on 300 words, starts showing problems around 1,000, and by 2,000 words the output has a completely different rhythm from the beginning to the end. is this a known problem and is there a workaround?

Most publicly documented approaches use some combination of perplexity and burstiness. Perplexity measures how predictable the text is relative to a language model’s expectations. Burstiness measures whether sentence complexity varies naturally or stays artificially uniform. AI text tends to be low-perplexity and low-burstiness compared to human writing. Disagreement between tools usually reflects different baseline models and training data, not just noise, though noise contributes too.