Do Methods to Jailbreak and Defend LLMs Generalize Across Languages?

arXiv — cs.CL•Wednesday, November 5, 2025 at 5:00:00 AM

A recent study published on arXiv investigates the generalizability of jailbreak methods and defenses for large language models (LLMs) across ten different languages. The research emphasizes the importance of systematically evaluating these techniques, as existing safety measures designed to prevent misuse can often be circumvented. By focusing on multiple linguistic contexts, the study aims to determine how effectively these methods perform beyond English, addressing a gap in current understanding. Although the investigation explores whether jailbreak and defense strategies generalize across languages, the findings remain uncertain regarding their universal applicability. This work contributes to ongoing discussions about the robustness and safety of LLMs, highlighting challenges in maintaining secure and reliable AI systems in diverse language environments. The study aligns with broader efforts to assess LLM vulnerabilities and improve safeguards in multilingual settings.

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