1 citations · 1 across the 10 of their papers we have counts for
11 papers
Precision over Scale: A Polish-Silesian Benchmark and a Translation System Outperforming Open-Source and Commercial Models
Grzegorz Kulik, Mikołaj Pokrywka, Adam Jatowt +1
Dialectal machine translation remains challenging due to limited data and strong linguistic variation not captured by standard benchmarks, which often assume standardized and well-…
Polish Medical Visual Question Answering: Vision-Language Models Underutilize Visual Evidence
Jakub Pokrywka, Łukasz Grzybowski, Antoni Lasik +3
We introduce a Polish-language medical visual question answering (VQA) benchmark, built from Polish Board Certification Examination questions for licensed physicians and dentists p…
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…
Reassessing High-Performing LLMs on Polish Medical Exams: True Competence or Bias-Driven Performance?
Antoni Lasik, Jakub Pokrywka, Łukasz Grzybowski +7
Large language models (LLMs) in medicine are mainly evaluated using multiple-choice question answering (MCQA), which can overestimate real clinical ability due to guessing strategi…
Multilingual Refusal Alignment for Safer Large Language Models
Aleksandra Krasnodębska, 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…
The LLM Effect on IR Benchmarks: A Meta-Analysis of Effectiveness, Baselines, and Contamination
Moritz Staudinger, Wojciech Kusa, Allan Hanbury
Benchmark collections have long enabled controlled comparison and cumulative progress in Information Retrieval (IR). However, prior meta-analyses have shown that reported effective…
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-…
Compare: A Framework for Scientific Comparisons
Moritz Staudinger, Wojciech Kusa, Matteo Cancellieri +3
Navigating the vast and rapidly increasing sea of academic publications to identify institutional synergies, benchmark research contributions and pinpoint key research contribution…
PL-Guard: Benchmarking Language Model Safety for Polish
Aleksandra Krasnodębska, Karolina Seweryn, Szymon Łukasik +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…
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
Mikołaj Pokrywka, Wojciech Kusa, Mieszko Rutkowski +1
Neural Machine Translation (NMT) has improved translation by using Transformer-based models, but it still struggles with word ambiguity and context. This problem is especially impo…
ASPIRE: Assistive System for Performance Evaluation in IR
Georgios Peikos, Wojciech Kusa, Symeon Symeonidis
Information Retrieval (IR) evaluation involves far more complexity than merely presenting performance measures in a table. Researchers often need to compare multiple models across…