Unverified50% confidenceFactExact time
The output of large language models is influenced by multiple stochastic factors including temperature, sampling strategy, context window, and model version updates, meaning the same prompt can produce significantly different text across different invocations.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/2/2026
First Seen
Valid until: 12/31/2026
Sources
Related Entities
Related Claims
Unverified当底层大语言模型进行版本更新时，即使提示词不变，输出分布也可能发生变化75% similarUnverified大语言模型本质上是概率性的，相同的输入可能产生不同的输出，这与传统软件的确定性行为截然不同73% similarVerifiedPerplexity measures a language model's ability to predict test text; the lower the value, the less surprised the model is by the text.70% similarVerifiedTypical characteristics of text output by mainstream large language models include well-structured sentence patterns, clear paragraph organization, frequent use of emphatic vocabulary, and explicit logical chains — a phenomenon researchers refer to as "stylistic bias."70% similarUnverified系统提示词的语言选择会影响输出风格，当系统提示词语言与用户输入语言不一致时会产生行为叠加效应69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/967230API
curl https://kongchang.com/api/v1/knowledge/claims/967230MCP
get_claim(id=967230)