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Harmony in Diversity: Multi-domain Contrastive Policy Optimization for Large Reasoning Models
Post-training via Reinforcement Learning (RL) has enabled Large Reasoning Models (LRMs) to achieve strong performance in individual domain. However, real-world applications increasingly require general-purpose reasoners rendering strong performance across diverse domains. Mixed-domain post-training
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