Why don't ML research agents overfit?

New research finds ML agents learn highly compressible strategies rather than memorizing data. Squeezing a successful agent’s strategy through an information bottleneck—down to about 16 tokens—still lets a fresh agent reproduce performance, showing compression distinguishes true generalization from overfitting.