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This paper introduces SSC-GRPO, a step-level reward optimization method that uses self-consistency scores across multiple rollouts to reduce context-sensitive factual hallucinations in LLM reasoning, achieving state-of-the-art performance on math reasoning and hallucination benchmarks.