Papers by Maciej Chrabaszcz

2 papers
PLLuM-Align: Polish Preference Dataset for Large Language Model Alignment (2025.emnlp-main)

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Challenge: Large language models generate preferred responses while avoiding harmful or inappropriate outputs, despite their ability to generate cross-language transferability.
Approach: They introduce the first Polish preference dataset PLLuM-Align, created entirely through human annotation to reflect Polish language and cultural nuances.
Outcome: The proposed dataset lays the groundwork for more aligned Polish LLMs and contributes to the broader goal of multilingual alignment in underrepresented languages.
Safety of Large Language Models Beyond English: A Systematic Literature Review of Risks, Biases, and Safeguards (2026.eacl-long)

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Challenge: Large language models (LLMs) have a growing number of applications that generate harmful, biased, or unsafe content.
Approach: They synthesize findings from recent studies that evaluate their robustness across languages . they highlight gaps in multilingual safety research and recommend future work .
Outcome: The systematic review examines the multilingual safety of large language models in English . it identifies challenges such as dataset availability and evaluation biases .

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