Unverified60% confidenceFactExact time
Large language models generate text in an autoregressive manner, where the production of each token depends on the context formed by all preceding tokens, following the chain rule of probability.
2
Sources
60%
Confidence
Long-term
Relevance
7/9/2026
First Seen
Sources
FTPO: A Training-Level Solution to AI Repetition Loops
hackernewshackernews7/7/2026
Related Claims
UnverifiedLarge language models use an autoregressive generation mechanism, sampling the next token at each step based solely on a probability distribution, with each token's generation conditioned on all preceding tokens to form a chain of probabilistic dependencies.83% similarVerifiedWhen generating each token, large language models perform probabilistic sampling over all possible next words in the vocabulary, rather than deterministically selecting a unique answer.80% similarUnverifiedAutoregressive models generate text token by token from left to right, and each step depends on the previously generated content.79% similarUnverified语言建模将一段文本的联合概率分解为每个词在其前文条件下的条件概率之积79% similar
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