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This article discusses the challenges and importance of evaluating the multilingual capabilities of large language models (LLMs) to ensure they meet safety and performance standards across different languages. It highlights the need for comprehensive evaluation frameworks and guardrails to address biases and ensure LLMs are safe and effective in diverse linguistic contexts.