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Related Questions
- What are some common types of out-of-distribution data that can affect model performance in prompt engineering?
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- What are some strategies for identifying and handling outliers in prompt engineering datasets?
- Can you explain the concept of data calibration and how it can be used to improve model performance in the presence of out-of-distribution data?
- What are some techniques for detecting and handling concept drift in prompt engineering models?
- How can transfer learning be used to adapt models to new out-of-distribution data?
- What are some best practices for evaluating model performance on out-of-distribution data in prompt engineering?
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