Unverified50% confidenceFactExact time
Rule drift refers to the phenomenon in which the underlying decision rules of an environment change non-explicitly over time; similar to concept drift, it requires the learning system to detect distribution changes and trigger model updates.
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Long-term
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10/20/2026
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Related Claims
UnverifiedBehavioral drift refers to changes in the model's output distribution on tasks it had already mastered or on irrelevant prompts after injecting new knowledge, and is typically measured using retained general-purpose prompts.75% similarUnverifiedModel behavior drift means that even if the code and prompts are unchanged, after the underlying model is silently updated, temperature parameters change, or context length is adjusted, the output distribution for the same input may also change.72% similarVerified模型漂移通常分为数据漂移和概念漂移两类，数据漂移指输入数据统计分布随时间变化，概念漂移指输入与输出关系本身发生变化71% similarVerifiedData drift or concept drift refers to the phenomenon where model performance degrades significantly when the real-world data distribution changes while the model is still trained on old data; the industry addresses this with continuous learning and active learning strategies.71% similarUnverifiedConcept drift refers to the statistical relationship between input data and the target variable changing over time, causing a previously trained model to gradually become ineffective; it is usually divided into three types: abrupt, gradual, and periodic.68% similar
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