
Large language models exhibit significant performance gaps across different languages, with high-resource languages like English significantly outperforming low-resource languages.


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quantifying-the-multilingual-performance-gaps-of-large-language-models-across-languages


Quantifying the Multilingual Performance Gaps of Large Language Models Across Languages


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LLM-as-a-Judge and reward models are widely used for evaluating large language models, but their effectiveness in non-English contexts remains largely unexplored. This study provides a comprehensive analysis of their performance on a new Korean meta-evaluation dataset, KUDGE, uncovering key insights on the transferability and limitations of these automated evaluators.


evaluating-the-effectiveness-of-llm-as-a-judge-and-reward-models-across-languages-insights-from-a-comprehensive-analysis-of-korean-meta-evaluation


Evaluating the Effectiveness of LLM-as-a-Judge and Reward Models Across Languages: Insights from a Comprehensive Analysis of Korean Meta-Evaluation
