Unverified50% confidenceFactExact time
输出生成是严格串行的自回归过程，每生成一个token都需要一次完整的模型前向传播
1
Sources
50%
Confidence
Long-term
Relevance
8/23/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAutoregressive generation refers to the model predicting the next token each time based on all previously generated tokens, progressively unfolding until a complete code block is generated78% similarUnverifiedModel generation is an autoregressive serial process that generates only one token at a time, causing the output phase to be insufficiently parallelizable and computationally more intensive than the input encoding phase.78% similarUnverifiedEach time a token is generated via a forward pass, the model must go through a complete multi-head attention computation and feed-forward network layers, with the amount of computation determined by the model's parameter scale73% similarUnverifiedAutoregressive models work by taking the output of the previous step as the input for the next step, generating sequences incrementally.73% 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73% similar
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