Adam Block

Agnostic smoothed online learning is now achievable without knowing the base measure or smoothing parameter, matching statistical learning's flexibility with online learning's robustness.

Counterintuitively, penalizing prediction error in language model rewards—instead of rewarding it—can drastically improve Best-of-N sampling by preventing reward hacking.