Unverified50% confidenceFactExact time
温度参数通过对 softmax 层的 logits 进行缩放来控制概率分布的尖锐程度，温度趋近于0时接近贪心解码
1
Sources
50%
Confidence
Long-term
Relevance
7/7/2026
First Seen
Sources
Taste-Skill: The Open-Source AI Taste Engine That Fights Generic AI-Generated Content
githubGitHub Trending7/5/2026
Related Claims
Unverified温度参数（Temperature）的数学本质是对Softmax函数输出的概率分布进行缩放，趋近于0时模型进行贪心解码81% similarVerifiedThe Temperature parameter acts on the softmax function output: when below 1, the probability distribution becomes sharper; when above 1, the distribution becomes flatter.80% similarVerifiedThe temperature parameter scales the Logits vector, and when temperature is 0, it degenerates into greedy decoding.80% similarVerifiedThe large model temperature parameter adjusts the flatness of the output probability distribution by dividing logits by the temperature value before applying softmax normalization.77% similarVerifiedThe Temperature parameter controls the randomness of LLM output; for code generation scenarios, a lower temperature value (such as 0.1) is typically recommended to obtain more deterministic and conservative results.76% similar
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