Unverified50% confidenceFactExact time
The model generates a sentence far faster than the full sentence can be played, so when the caller interrupts mid-sentence, the model's generation has long since finished, but the caller has only received part of it.
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWhen large models generate text, they do not generate an entire sentence at once; instead, they generate tokens one by one, continuously predicting the next token and adding it to the context in a loop.73% similarUnverifiedThe inference process of large language models is autoregressive, and the number of output Tokens is almost linearly correlated with response latency.71% similarUnverified用户输入的每个词都会成为模型的上下文，改变模型接收到的数学输入，进而影响解码阶段的概率分布和输出内容69% similarUnverifiedTokens per second (tokens/s) measures throughput in the decoding stage and does not directly equal the model's performance on complex reasoning tasks; a high-speed version may perform extremely well on tasks such as code completion but is not necessarily better than the main model on long-chain reasoning tasks.69% similarUnverifiedWhen a model becomes confused during a multi-turn conversation, stopping the conversation, clearing the context, and consolidating all known information into a single complete single-turn instruction yields noticeably better model performance.69% similar
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