Unverified50% confidenceOpinionExact time
语言的语法结构越简单、惯用模式越统一，大模型在每一步预测中面临的困惑度越低，生成正确序列的概率越高
1
Sources
50%
Confidence
Long-term
Relevance
8/19/2026
First Seen
Sources
Related Claims
UnverifiedLarge language models predict the next token one at a time through an autoregressive generation mechanism, and are naturally inclined to generate more complete rather than more concise code.78% similarVerifiedThe essence of large language models is learning the conditional probability distribution of what the next word is given the preceding text78% similarUnverifiedWhen generating each token, large language models perform probabilistic sampling over all possible next words in the vocabulary, rather than deterministically selecting a unique answer.78% similarUnverified自回归多模态模型借鉴语言模型的token预测机制，在理解复杂文字指令和保持角色一致性方面更具优势77% similar
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