Unverified50% confidenceFactExact time
Autoregressive models generate token by token, with each step conditioned on the previously generated content.
1
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50%
Confidence
Long-term
Relevance
11/2/2026
First Seen
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Related Claims
VerifiedSpeculative decoding generates candidate tokens through a lightweight draft model, with the main model verifying them in parallel in a single forward pass, accepting tokens that conform to the distribution and regenerating from the first rejected position.77% similarUnverifiedOne-step parallel generation requires the model to produce all tokens simultaneously in a single forward pass, and conventional approaches make it difficult to inject a preference over prediction order.76% similarUnverifiedFor each token generated or processed, one forward pass must be executed, and its computational cost is roughly proportional to the number of model parameters.76% 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.76% similarUnverifiedIn generative large models, a single forward pass usually produces only one token, and to obtain a complete output the result must be fed back into the input and called repeatedly, i.e., autoregressive decoding.76% similar
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