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CroCo: Cross-Lingual Contrastive Preference Tuning on Self-Generations
Prior work establishes that controlled contrastiveness between self-generated responses from large language models, set via reward scores, improves downstream preference tuning in English. We extend this method to multiple languages and evaluate two models across a total of 14 high and low-resource
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