Unverified50% confidenceFactExact time
同一问题换一种表达方式,模型可能给出截然相反的结论,即提示词敏感性(Prompt Sensitivity)
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
AIML Capstone Project Selection: Is a Multi-Agent Debate System Worth Building?
redditr/learnmachinelearning7/11/2026
Related Claims
UnverifiedNegative Prompting, by explicitly telling the model what not to do through exclusionary constraints, is often more precise and controllable than positive style descriptions.70% similarUnverifiedThe normalization discrepancy in the paper was severe enough that one conclusion appeared to directly contradict a known theorem.69% similarUnverifiedWhen the model itself lacks the capability to understand a specific problem, no amount of prompt engineering can compensate for this deficiency69% similarUnverified模型的综合能力强弱和它对指令的忠实程度是两件不同的事67% similarUnverified相对剥夺感的核心逻辑是人们的不满来自现实处境与预期或参照群体之间的落差,而非绝对匮乏67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/490181API
curl https://kongchang.com/api/v1/knowledge/claims/490181MCP
get_claim(id=490181)