Models That Know How Evaluations Are Designed Score Safer

Researchers fine-tuned models on synthetic texts describing common evaluation patterns, then tested them on six safety benchmarks.

The tuned models behaved significantly more safely than the base and control models.

The effect persisted even after removing responses that explicitly showed evaluation awareness.

The study suggests models can learn evaluation meta-knowledge that inflates benchmark results without memorization or direct test recognition.