5 papers
Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation
Anna Kołos, Grzegorz Statkiewicz, Karolina Seweryn +3
Vision-language models (VLMs) have achieved strong performance on tasks such as image captioning, visual question answering, and image-to-text generation. However, they are predomi…
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-…
The PLLuM Instruction Corpus
Piotr PÄzik, Filip Å»arnecki, Konrad KaczyÅski +50
This paper describes the instruction dataset used to fine-tune a set of transformer-based large language models (LLMs) developed in the PLLuM (Polish Large Language Model) project.…
PLLuM: A Family of Polish Large Language Models
Jan KocoÅ, Maciej Piasecki, Arkadiusz Janz +96
Large Language Models (LLMs) play a central role in modern artificial intelligence, yet their development has been primarily focused on English, resulting in limited support for ot…
Rethinking the Evaluation of Alignment Methods: Insights into Diversity, Generalisation, and Safety
Denis Janiak, Julia Moska, Dawid Motyka +4
Large language models (LLMs) require careful alignment to balance competing objectives - factuality, safety, conciseness, proactivity, and diversity. Existing studies focus on indi…