BabelSafe: A Policy-Grounded Multilingual Safety Benchmark for LLMs
As Large Language Models (LLMs) are increasingly deployed in cross-linguistic contexts, ensuring safety across diverse regulatory and cultural environments has become a critical challenge. However, existing multilingual benchmarks largely rely on general risk taxonomies and machine-translated data, limiting evaluation to predefined risk categories and providing insufficient coverage of region-specific regulatory requirements and cultural contexts. To bridge these gaps, we introduce BabelSafe, a policy-grounded multilingual safety benchmark covering 13 language settings. BabelSafe is constructed from regional regulatory sources, with risk categories and fine-grained rules extracted from ju...
| Authors | Yunhan Zhao, Zhaorun Chen, Xingjun Ma et al. |
|---|---|
| Primary category | cs.CL |
| Published | 1 May 2026 |
| Last updated at source | 27 September 2026 |
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