Unverified50% confidenceOpinionExact time
The suppressed rare-class knowledge has not disappeared from the model; it is merely difficult to invoke under a particular inference prompt.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedWhen the model itself lacks the capability to understand a specific problem, no amount of prompt engineering can compensate for this deficiency79% similarUnverifiedModels have no confidence-gating mechanism during generation and cannot determine whether they know something; when faced with a knowledge gap, they do not stop to express uncertainty but instead continue generating the statistically most fluent continuation.79% similarUnverifiedAblation experiments show that relying solely on reasoning yields no significant improvement in accuracy for rare entities.76% similarUnverifiedPrompts cannot supply a model with knowledge it does not already possess; they can only make it more honestly silent when it is ignorant.75% similarVerifiedWhen a model lacks up-to-date information, it may not admit ignorance, but instead fabricate seemingly plausible yet factually incorrect answers (hallucinations).75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1046227API
curl https://kongchang.com/api/v1/knowledge/claims/1046227MCP
get_claim(id=1046227)