Unverified50% confidenceFactExact time
LLMs generate text in an autoregressive manner, generating only one token at a time and appending it to the input sequence, requiring 100 complete forward passes through the model to generate 100 tokens.
1
Sources
50%
Confidence
Long-term
Relevance
9/4/2026
First Seen
Sources
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Related Claims
UnverifiedAutoregressive models formulate text generation as a chain of conditional probabilities; generating a text of 1,000 tokens requires 1,000 forward inference passes, and the computational load of each inference increases as the context window grows.69% similarUnverifiedLarge 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.66% similarVerifiedLLMs generate text in an autoregressive manner based on the Transformer architecture, predicting only one token per forward pass and then appending that token to the input sequence before predicting the next token.63% similarUnverified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63% similar
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