3 papers
cs.CL2025
The PLLuM Instruction Corpus
Piotr Pęzik, Filip Żarnecki, Konrad Kaczyński +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.…
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.LG2025
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…