Unverified50% confidenceFactExact time
The sampling mentioned in decoding randomness includes temperature scaling, top-k and top-p, aimed at avoiding stiff, repetitive output, at the cost that low-probability tokens are occasionally selected and errors can be plausibly continued.
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10/14/2026
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VerifiedTemperature controls the flatness of the sampling distribution; a higher value tends toward selecting lower-probability words, while Top-p dynamically narrows the candidate vocabulary set through a cumulative probability threshold.79% similarUnverifiedThe temperature parameter controls sampling randomness: the lower the value, the more deterministic the output; near 0, the model tends to choose the highest-probability token, suitable for code generation, SQL generation, and other scenarios requiring reproducibility.76% similarVerifiedThe non-determinism of LLMs stems from sampling strategies; the Temperature parameter controls the randomness of the output distribution, while Top-p and Top-k further constrain the range of candidate tokens.74% similarUnverifiedTop-p（核采样）通过限定候选token的累积概率范围来控制输出多样性，与Temperature配合使用可实现更精细的输出调节73% similar
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