Unverified50% confidenceFactExact time
自回归模型生成长度为 N 的文本需要 N 次前向传播，推理延迟随文本长度线性增长
1
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50%
Confidence
Long-term
Relevance
8/22/2026
First Seen
Sources
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Related Claims
UnverifiedLLMs generate text in an autoregressive manner, producing only one token at a time, requiring N forward inference passes to generate N tokens, with latency scaling linearly with output length.68% similarUnverified大模型推理的自回归生成需要逐Token串行输出，生成N个Token需要N次前向传播67% similarUnverifiedN-gram统计语言模型通过相邻词的条件概率捕捉局部上下文，受限于固定窗口大小，无法处理长距离依赖，参数量随词汇表指数膨胀65% 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.63% similarUnverifiedThe core idea of the N-gram model is to use the preceding N-1 words to predict the probability of the N-th word.63% similar
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