internalization

This paper introduces ICRL, a framework that jointly trains a solver and critic with reinforcement learning to internalize critique guidance, enabling the solver to improve without external critique. It uses distribution calibration and role-wise group advantage estimation, achieving 6-7 point gains over GRPO on agentic and mathematical reasoning tasks.