activity
20242026
collaborators

5 papers

cs.CL2026

Long-Context Encoder Models for Polish Language Understanding

Sławomir Dadas, Rafał Poświata, Marek Kozłowski +4

While decoder-only Large Language Models (LLMs) have recently dominated the NLP landscape, encoder-only architectures remain a cost-effective and parameter-efficient standard for d…

cs.CL2025

PLLuM: A Family of Polish Large Language Models

Jan Kocoń, 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…

cs.CL2025

Unveiling Dual Quality in Product Reviews: An NLP-Based Approach

Rafał Poświata, Marcin Michał Mirończuk, Sławomir Dadas +2

Consumers often face inconsistent product quality, particularly when identical products vary between markets, a situation known as the dual quality problem. To identify and address…

cs.CL2025

Evaluating Polish linguistic and cultural competency in large language models

Sławomir Dadas, Małgorzata Grębowiec, Michał Perełkiewicz +1

Large language models (LLMs) are becoming increasingly proficient in processing and generating multilingual texts, which allows them to address real-world problems more effectively…

cs.CL2024

Assessing generalization capability of text ranking models in Polish

Sławomir Dadas, Małgorzata Grębowiec

Retrieval-augmented generation (RAG) is becoming an increasingly popular technique for integrating internal knowledge bases with large language models. In a typical RAG pipeline, t…