Verified70% confidenceFactExact time
The randomness of AI large language model outputs stems from the temperature parameter and sampling strategy; when generating each token, the model is essentially performing probabilistic sampling.
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70%
Confidence
Long-term
Relevance
7/15/2026
First Seen
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Related Claims
VerifiedWhen a large language model generates each token, it samples from a probability distribution; the temperature parameter controls the degree of randomness—higher temperature produces more diverse outputs, while lower temperature produces more deterministic ones.84% similarVerifiedLarge language models are based on the Transformer architecture, and their output is essentially a probabilistic sampling process, with the Temperature parameter controlling the randomness of sampling.80% similarVerifiedThe output of large language models is inherently probabilistic, and parameters such as sampling temperature and Top-P mean the model may generate different content each time, posing a challenge for software testing.78% similarUnverifiedAgent系统依赖大型语言模型进行动态决策，其行为具有由temperature参数控制的采样过程决定的随机性77% similar
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