Amazon Science asks why ML research agents don't overfit
Amazon Science blog post examines why machine learning research agents avoid overfitting despite iterating against the same benchmarks, which normally turns a held-out test set into part of the training procedure. It contrasts the standard validation/test split with the iterative improvement loop real ML research uses.
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