Evaluation Sets and Regression Testing

To track user complaints To determine if changes will affect quality before user exposure To measure performance metrics after deployment To generate new training data for the model

They represent unimportant questions to avoid They help define model architecture They guide the expected behavior of a system in response to specific queries They should be removed from the evaluation process

The test is ignored The production release proceeds anyway The build fails and the changes are not deployed to production The model receives automatic retraining

By storing outdated golden questions By providing new metrics that do not relate to production performance By reflecting real-world failures and refusals to update the evaluation set By disconnecting tests from production data