Sch\"utzen: Evaluating LLM Safety in Bulgarian and German Contexts
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Computer Science > Computation and Language
Title:Schützen: Evaluating LLM Safety in Bulgarian and German Contexts
Abstract:Large language models are increasingly deployed across professional domains, bringing hard-to-predict risks, including the generation of harmful or disrespectful content. Although substantial progress has been made in developing safety evaluation datasets, existing resources remain overwhelmingly English- and Chinese-centric. This limitation is particularly pronounced when evaluating languages that operate within shared sociocultural, legal, and ethical contexts. To address this gap, we introduce Schützen: a German--Bulgarian safety dataset designed to assess model answerability under risk, covering both a low-resource language (Bulgarian) and a high-resource language (German). Experiments with multilingual and language-specific LLMs reveal pronounced cross-language differences in safety behavior, highlighting the necessity of tailored, region-specific evaluation resources to support the responsible deployment of LLMs in Germany and Bulgaria. Datasets and code are available at this https URL. Warning: this paper contains examples that may be offensive, harmful, or biased.
| Comments: | 19 pages, 13 tables, 12 figures |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2606.11316 [cs.CL] |
| (or arXiv:2606.11316v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.11316
arXiv-issued DOI via DataCite (pending registration)
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