Unverified60% confidenceFactExact time
Due to the stochastic nature of large language model outputs, it is difficult for ordinary users to determine the underlying model version from a single conversation.
2
Sources
60%
Confidence
Long-term
Relevance
8/13/2026
First Seen
Sources
Related Claims
Unverified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78% similarUnverifiedA/B test outputs for large language models are highly random and subjective, and the same prompt may produce completely different results across two separate conversations.77% similarUnverifiedLanguage model outputs are probabilistic and semantically ambiguous, making it difficult to measure quality with precise assertions, which poses challenges for migrating TDD concepts to the prompt engineering domain.75% similarUnverified大语言模型每次对话独立，无法对整个代码库形成持久认知模型，导致不同会话生成的代码在架构风格、命名规范、错误处理策略上存在系统性不一致74% similarUnverified大语言模型的输出天然具有随机性，同一问题问十次可能得到十个措辞不同、推荐品牌各异的答案74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/742661API
curl https://kongchang.com/api/v1/knowledge/claims/742661MCP
get_claim(id=742661)