3 papers
cs.CL2026
How to Evaluate When You Don't Know How to Evaluate? Choosing Reliable Setups for Base Language Model Benchmarking
Shenbin Qian, David Samuel, Jindřich Helcl +2
Evaluation of large language models (LLMs) remains largely pre-scientific: it involves many design decisions, with little guidance on how to make them. These choices can substantia…
cs.CL2025
The Impact of Copyrighted Material on Large Language Models: A Norwegian Perspective
Javier de la Rosa, Vladislav Mikhailov, Lemei Zhang +16
The use of copyrighted materials in training language models raises critical legal and ethical questions. This paper presents a framework for and the results of empirically assessi…
cs.CL2024
Small Languages, Big Models: A Study of Continual Training on Languages of Norway
David Samuel, Vladislav Mikhailov, Erik Velldal +4
Training large language models requires vast amounts of data, posing a challenge for less widely spoken languages like Norwegian and even more so for truly low-resource languages l…