Validation
Measure the changed system on separate cases.
Compare a baseline with a later run while keeping the final evaluation outside the development process.
What makes the comparison useful?
Record the model, system settings, intervention, dataset version, and grading rules. Compare both aggregate results and the failure patterns that motivated the change.
How we work
Review overlap between evaluation and remediation data. If validation cases guide prompt tuning or checkpoint selection, they are serving as development data and should be described that way.
Scope and limits
A split label alone does not prove independence. Observed changes do not guarantee causality or performance on every future task.