AlbanianLLMSafety: A Safety Evaluation Dataset for Large Language Models in Albanian
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Computer Science > Computation and Language
Title:AlbanianLLMSafety: A Safety Evaluation Dataset for Large Language Models in Albanian
Abstract:Safety evaluation of Large Language Models (LLMs) has largely focused on high-resource languages, leaving low-resource languages critically underserved. We present AlbanianLLMSafety, the first publicly available safety evaluation dataset for LLMs in Albanian, a linguistically distinct low-resource language with approximately 7.5 million speakers across Albania, Kosovo, North Macedonia, and the diaspora. The dataset contains 2,951 prompts spanning 11 safety categories, including self-harm, violence, racist content, child exploitation, and radicalization, with an average of 268 prompts per category. Each prompt is provided in Albanian with an English reference translation and a detailed category label. This resource addresses a significant gap in safety evaluation infrastruc-ture for low-resource languages and provides an essential benchmark for developing safer, more inclusive LLMs. The dataset will be provided upon request to support safety evaluation, fine-tuning, red-teaming, and guardrail development for Albanian-speaking communities.
| Comments: | Accepted at SIGUL2026 Workshop co-located with LREC2026 |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.26954 [cs.CL] |
| (or arXiv:2605.26954v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.26954
arXiv-issued DOI via DataCite (pending registration)
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