The ensemble diversity point is underrated. Most teams pick one architecture and ship it, so the finding that architectural variation beats random seeds is interesting but hard to act on in practice. The more useful takeaway: low-data regimes expose every bad design decision you normally paper over with more tokens. It's basically a forcing function for understanding what actually drives model quality vs. what's just scale noise.