Beyond Scalar Critics: A Distributional Perspective on Reinforcement Learning with Verifiable Rewards for LLMs
DistRLVR is a distributional RL framework for LLM post-training with verifiable rewards that models token-level return distributions and uses tail-aware advantages to improve sample efficiency and reasoning performance.
Jan 1, 2026