skLEP: A Slovak General Language Understanding Benchmark

Fuente: arXiv
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Main Authors: Šuppa, Marek, Ridzik, Andrej, Hládek, Daniel, Javůrek, Tomáš, Ondrejová, Viktória, Sásiková, Kristína, Tamajka, Martin, Šimko, Marián
Format: Preprint
Published: 2025
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author Šuppa, Marek
Ridzik, Andrej
Hládek, Daniel
Javůrek, Tomáš
Ondrejová, Viktória
Sásiková, Kristína
Tamajka, Martin
Šimko, Marián
author_facet Šuppa, Marek
Ridzik, Andrej
Hládek, Daniel
Javůrek, Tomáš
Ondrejová, Viktória
Sásiková, Kristína
Tamajka, Martin
Šimko, Marián
contents In this work, we introduce skLEP, the first comprehensive benchmark specifically designed for evaluating Slovak natural language understanding (NLU) models. We have compiled skLEP to encompass nine diverse tasks that span token-level, sentence-pair, and document-level challenges, thereby offering a thorough assessment of model capabilities. To create this benchmark, we curated new, original datasets tailored for Slovak and meticulously translated established English NLU resources. Within this paper, we also present the first systematic and extensive evaluation of a wide array of Slovak-specific, multilingual, and English pre-trained language models using the skLEP tasks. Finally, we also release the complete benchmark data, an open-source toolkit facilitating both fine-tuning and evaluation of models, and a public leaderboard at https://github.com/slovak-nlp/sklep in the hopes of fostering reproducibility and drive future research in Slovak NLU.
format Preprint
id arxiv_https___arxiv_org_abs_2506_21508
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle skLEP: A Slovak General Language Understanding Benchmark
Šuppa, Marek
Ridzik, Andrej
Hládek, Daniel
Javůrek, Tomáš
Ondrejová, Viktória
Sásiková, Kristína
Tamajka, Martin
Šimko, Marián
Computation and Language
Artificial Intelligence
Information Retrieval
Machine Learning
68T50
I.2.7
In this work, we introduce skLEP, the first comprehensive benchmark specifically designed for evaluating Slovak natural language understanding (NLU) models. We have compiled skLEP to encompass nine diverse tasks that span token-level, sentence-pair, and document-level challenges, thereby offering a thorough assessment of model capabilities. To create this benchmark, we curated new, original datasets tailored for Slovak and meticulously translated established English NLU resources. Within this paper, we also present the first systematic and extensive evaluation of a wide array of Slovak-specific, multilingual, and English pre-trained language models using the skLEP tasks. Finally, we also release the complete benchmark data, an open-source toolkit facilitating both fine-tuning and evaluation of models, and a public leaderboard at https://github.com/slovak-nlp/sklep in the hopes of fostering reproducibility and drive future research in Slovak NLU.
title skLEP: A Slovak General Language Understanding Benchmark
topic Computation and Language
Artificial Intelligence
Information Retrieval
Machine Learning
68T50
I.2.7
url https://arxiv.org/abs/2506.21508