Data contamination

Data contamination is when examples from an evaluation benchmark appear in a model's training data, inflating its scores because the model may have memorized answers rather than learned the skill.

Data contamination sits in the Evaluation & safety part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.

Also called Benchmark contamination, Test set contamination.