The Ledger
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Alexandr Wang: Academic AI benchmarks are contaminated and models are overfit.
“The academic benchmarks that are what the industry used to measure the performance of these algorithms are fraught with issues. Many of the models are overfit on these benchmarks. They're sort of in the training data sets of these models.”
Alexandr Wang: Held-out benchmarks reveal several AI models underperform their reported scores.
“So we, one of the things we did is we published DSM-I-K, which was a held out eval. So we basically produced a new evaluation of the math capabilities of models. That there's no way it would ever exist in the training data set to really see how much of the, ho…”