The CAST method enhances Group Relative Policy Optimization (GRPO) in reinforcement learning by introducing an answer-free self-distillation approach that improves token-level guidance based on trajectory correctness. This innovation aims to address the limitations of existing methods, potentially leading to more effective reasoning in large language models.