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Research identifies excess vocabulary like "delve" and "tapestry" as statistical markers of LLM-generated text, alongside name priors and hedging patterns. These cues stem from post-training preferences and offer probabilistic detection, not certainty. Detection tools often misclassify human writing as AI-generated.
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