7 papers
HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models
Stephan Oepen, Nikolay Arefev, Mikko Aulamo +29
We present an ongoing initiative to provide open, very large, high-quality, and richly annotated textual datasets for almost 200 languages. At 30 trillion tokens, this is likely th…
NorEval: A Norwegian Language Understanding and Generation Evaluation Benchmark
Vladislav Mikhailov, Tita Enstad, David Samuel +4
This paper introduces NorEval, a new and comprehensive evaluation suite for large-scale standardized benchmarking of Norwegian generative language models (LMs). NorEval consists of…
An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)
Laurie Burchell, Ona de Gibert, Nikolay Arefyev +32
Training state-of-the-art large language models requires vast amounts of clean and diverse textual data. However, building suitable multilingual datasets remains a challenge. In th…
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…
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…
A Collection of Question Answering Datasets for Norwegian
Vladislav Mikhailov, Petter Mæhlum, Victoria Ovedie Chruickshank Langø +2
This paper introduces a new suite of question answering datasets for Norwegian; NorOpenBookQA, NorCommonSenseQA, NorTruthfulQA, and NRK-Quiz-QA. The data covers a wide range of ski…