arXiv AI
SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning
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SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning
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Rethinking Reward Supervision: Rubric-Conditioned Self-Distillation
Post-training of reasoning language models is commonly driven by supervised distillation and reinforcement learning with verifiable rewards. Distillation often relies on chain-of-thought annotations that are expensive to obtain and may themselves be noisy, incomplete, or partially incorrect; even when the final solution is correct, an imperfect rationale can interfere with learning.