Learning to Reason from Reference Samples Alone: Reinforced Adversarial Learning for Modern LLM Post-Training

In many settings where LLM post-training is desirable, high-quality answers are recognizable but difficult to score with explicit rewards. Reinforcement learning with verifiable rewards (RLVR) is limited to tasks where an explicit correctness signal is available. Prior adversarial approaches to trai