Expired50% confidenceFactTime unknown
In autoregressive generation, the model produces tokens one by one and never thinks through the entire answer before speaking
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
AI Hallucinations: Why Large Language Models Inevitably "Make Things Up" and How to Deal With It
bilibili老傅1024
Related Claims
UnverifiedSome AI models incorporate 'thinking tokens' mechanisms, performing internal reasoning steps before generating the final answer70% 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.69% 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.67% similarUnverifiedThe inference speed of large language models is constrained by the nature of autoregressive generation, which can only produce one token at a time and depends on all preceding tokens, making true parallelization impossible.66% similarUnverifiedWhen a prompt is entered, the model predicts the most likely next token based on context, rather than truly understanding the semantics.66% similar
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