AINeutralarXiv – CS AI · 14h ago6/10
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Source-Grounded Semantic Reinforcement Learning for Low-Resource Target-Language Generation
Researchers introduce Source-Grounded Semantic Reinforcement Learning (SG-SRL), a framework that leverages abundant source-language monolingual data to improve low-resource target-language generation through cross-lingual semantic rewards. The approach demonstrates significant gains in semantic grounding and factual coverage while maintaining fluency through a lightweight recovery stage.