Ratio-Variance Regularized Policy Optimization

ArXi:2605.26784v1 Announce Type: cross Standard on-policy reinforcement learning relies on heuristic clipping to enforce trust regions, but this mechanism imposes a severe cost by indiscriminately truncating high-return yet high-divergence updates. We nstrate that explicitly cons