Unverified50% confidenceFactExact time
When generating text, language models default to selecting word sequences with higher conditional probability.
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50%
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Long-term
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9/22/2026
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VerifiedPerplexity measures a language model's ability to predict test text; the lower the value, the less surprised the model is by the text.79% similarVerifiedTypical characteristics of text output by mainstream large language models include well-structured sentence patterns, clear paragraph organization, frequent use of emphatic vocabulary, and explicit logical chains — a phenomenon researchers refer to as "stylistic bias."77% similarUnverifiedText generated by large language models tends to have low perplexity, with word choices that are overly consistent with probabilistic expectations, lacking the unexpectedness of human writing.76% similarVerifiedLarge language models are trained on vast corpora of text data and learn to predict the probability distribution of the next word76% similarUnverifiedLarge language models autoregressively predict the next highest-probability token, causing AI-generated text to have low perplexity.76% similar
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