Unverified50% confidenceFactExact time
Autoregressive models work by taking the output of the previous step as the input for the next step, generating sequences incrementally.
1
Sources
50%
Confidence
Long-term
Relevance
8/8/2026
First Seen
Sources
往返一致性：让扩散模型自己预测误差的自监督方法
Related Claims
UnverifiedWord-by-word generation is technically called autoregressive generation, where the token generated at each step is appended back to the input sequence as the condition for the next prediction76% similarUnverifiedAutoregressive 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 generated75% similarUnverified大模型推理的本质是自回归生成，即不断预测下一个token72% similarUnverifiedModel steering influences model output behavior during inference by directly modifying the activation vectors of intermediate layers, without modifying weights.72% similarUnverifiedWhen a prompt is entered, the model predicts the most likely next token based on context, rather than truly understanding the semantics.70% similar
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