Localizing judge prompts to five languages shows that LLM backbones interact with language in agent-as-a-judge evaluations, inverting rankings and revealing no universal best model with low inter-judge agreement.
How reliable is multilingual LLM -as-a-judge? In Findings of the Association for Computational Linguistics: EMNLP 2025 , pp.\ 11040--11053, Suzhou, China
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Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation
Localizing judge prompts to five languages shows that LLM backbones interact with language in agent-as-a-judge evaluations, inverting rankings and revealing no universal best model with low inter-judge agreement.