Unverified50% confidenceFactExact time
Traditional large language models are fundamentally predicting the next token and outputting natural language, requiring an additional layer (such as outputting JSON or function calls) to execute tasks.
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50%
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Long-term
Relevance
9/19/2026
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Related Claims
UnverifiedModern large language models generate code in an auto-regressive manner, predicting the next token each time by referencing only the existing context.74% similarVerified大语言模型本质上是一个基于概率的文本预测系统，其核心机制是「下一个词预测」（Next Token Prediction），并不真正理解语义72% similarUnverified大语言模型是无状态的文本预测系统，每次推理调用仅接收当前输入的Token序列，不存储跨请求的持久化状态71% similarVerifiedThe token generation process of large language models is serial, based on an autoregressive mechanism, where each token's generation depends on the previous token.71% similarUnverifiedLarge 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.71% similar
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