Unverified50% confidenceFactExact time
Data distribution drift falls into three types—covariate shift, prior probability shift, and concept drift—of which concept drift is the most insidious and dangerous.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedPrompt engineering has three major limitations: prompt drift, high cross-model migration costs, and the inability to manage versions.65% similarUnverifiedThe larger the model, the more dispersed the safety alignment behavioral distribution is in the weight space, and the greater the difficulty of precisely removing it.65% similarUnverifiedFor data drift, multi-level alert thresholds can be set: mild drift triggers a warning, moderate drift triggers incremental retraining, and severe drift triggers full retraining and activates a fallback strategy.65% similarUnverifiedClassifiers in safety guardrails are probabilistic models with a tradeoff between false positives and false negatives; setting the threshold too low leads to excessive blocking.64% similarUnverified在长时间自主运行场景中，模型可能通过上下文积累逐渐偏离安全边界，这被研究者称为'对齐漂移'（alignment drift）63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/892992API
curl https://kongchang.com/api/v1/knowledge/claims/892992MCP
get_claim(id=892992)