Unverified50% confidenceFactExact time
LLM judge results are affected by factors such as temperature, prompt wording, and model version updates, causing the same set of test cases to potentially produce different conclusions when run at different times.
1
Sources
50%
Confidence
Long-term
Relevance
9/21/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSummaries generated by LLMs are probabilistic; the same input may produce different results at different temperature settings, posing a reproducibility risk.78% similarUnverifiedLLM在不同温度参数、上下文长度、随机种子下可能对同一攻击payload给出截然不同的响应，因此LLM安全测试的通过标准本质上是统计性的77% similarUnverifiedDifferences in test design, prompting methods, and model versions can lead to drastically different evaluation conclusions.75% similarUnverifiedThe choice of LLM judge has a significant impact on the final research conclusions, and using a lower-quality LLM as the judge may overestimate the intensity of context-memory conflicts.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/937710API
curl https://kongchang.com/api/v1/knowledge/claims/937710MCP
get_claim(id=937710)