AIBullisharXiv – CS AI · Mar 126/10
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CLIPO: Contrastive Learning in Policy Optimization Generalizes RLVR
Researchers introduce CLIPO (Contrastive Learning in Policy Optimization), a new method that improves upon Reinforcement Learning with Verifiable Rewards (RLVR) for training Large Language Models. CLIPO addresses hallucination and answer-copying issues by incorporating contrastive learning to better capture correct reasoning patterns across multiple solution paths.