3 papers
cs.CL2026
Multilingual Refusal Alignment for Safer Large Language Models
Aleksandra KrasnodÄbska, Wojciech Kusa, Aldo Lipani
As Large Language Models (LLMs) are deployed globally, ensuring their safety and alignment across multiple languages becomes paramount. However, safety behaviors often vary unpredi…
cs.CL2026
Annotation-Efficient Vision-Language Model Adaptation to the Polish Language Using the LLaVA Framework
Grzegorz Statkiewicz, Alicja Dobrzeniecka, Karolina Seweryn +5
Most vision-language models (VLMs) are trained on English-centric data, limiting their performance in other languages and cultural contexts. This restricts their usability for non-…
cs.CL2025
PL-Guard: Benchmarking Language Model Safety for Polish
Aleksandra KrasnodÄbska, Karolina Seweryn, Szymon Åukasik +1
Despite increasing efforts to ensure the safety of large language models (LLMs), most existing safety assessments and moderation tools remain heavily biased toward English and othe…