AIBullisharXiv – CS AI · 7h ago7/10
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EMCEE: Improving Multilingual Capability of LLMs via Bridging Knowledge and Reasoning with Extracted Synthetic Multilingual Context
Researchers introduce EMCEE, a framework that improves Large Language Models' multilingual performance by extracting and leveraging language-specific knowledge embedded within the models themselves. The method achieves 16.4% average improvement across multilingual benchmarks and 31.7% gains for low-resource languages, addressing the persistent challenge of English-centric LLM training.