Benchmarking Abstractive Summarisation: A Dataset of Human-authored Summaries of Norwegian News Articles

Fuente: arXiv
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Auteurs principaux: Touileb, Samia, Mikhailov, Vladislav, Kroka, Marie, Øvrelid, Lilja, Velldal, Erik
Format: Preprint
Publié: 2025
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author Touileb, Samia
Mikhailov, Vladislav
Kroka, Marie
Øvrelid, Lilja
Velldal, Erik
author_facet Touileb, Samia
Mikhailov, Vladislav
Kroka, Marie
Øvrelid, Lilja
Velldal, Erik
contents We introduce a dataset of high-quality human-authored summaries of news articles in Norwegian. The dataset is intended for benchmarking the abstractive summarisation capabilities of generative language models. Each document in the dataset is provided with three different candidate gold-standard summaries written by native Norwegian speakers, and all summaries are provided in both of the written variants of Norwegian -- Bokmål and Nynorsk. The paper describes details on the data creation effort as well as an evaluation of existing open LLMs for Norwegian on the dataset. We also provide insights from a manual human evaluation, comparing human-authored to model-generated summaries. Our results indicate that the dataset provides a challenging LLM benchmark for Norwegian summarisation capabilities
format Preprint
id arxiv_https___arxiv_org_abs_2501_07718
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Benchmarking Abstractive Summarisation: A Dataset of Human-authored Summaries of Norwegian News Articles
Touileb, Samia
Mikhailov, Vladislav
Kroka, Marie
Øvrelid, Lilja
Velldal, Erik
Computation and Language
We introduce a dataset of high-quality human-authored summaries of news articles in Norwegian. The dataset is intended for benchmarking the abstractive summarisation capabilities of generative language models. Each document in the dataset is provided with three different candidate gold-standard summaries written by native Norwegian speakers, and all summaries are provided in both of the written variants of Norwegian -- Bokmål and Nynorsk. The paper describes details on the data creation effort as well as an evaluation of existing open LLMs for Norwegian on the dataset. We also provide insights from a manual human evaluation, comparing human-authored to model-generated summaries. Our results indicate that the dataset provides a challenging LLM benchmark for Norwegian summarisation capabilities
title Benchmarking Abstractive Summarisation: A Dataset of Human-authored Summaries of Norwegian News Articles
topic Computation and Language
url https://arxiv.org/abs/2501.07718