Amazon Science says research explains why benchmark reuse largely avoids overfitting
Years of iterating against the same benchmarks should produce overfitting—fitting too closely to those tests—but largely don't, Amazon Science says.
TLDR
Amazon Science describes new research pointing to a compression bottleneck as an explanation for why repeated benchmark use largely doesn't produce overfitting. Strategies that generalize can be expressed in forms too compact to allow memorization, it says, while strategies that overfit don't survive that bottleneck.
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