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skLEP: A Slovak General Language Understanding Benchmark

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AUSPT99V2" target="_blank" >RIV/00216208:11320/26:USPT99V2 - isvavai.cz</a>

  • Result on the web

    <a href="https://aclanthology.org/2025.findings-acl.1371/" target="_blank" >https://aclanthology.org/2025.findings-acl.1371/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.48550/arXiv.2506.21508" target="_blank" >10.48550/arXiv.2506.21508</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    skLEP: A Slovak General Language Understanding Benchmark

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Findings of the Association for Computational Linguistics

  • ISBN

    979-8-89176-256-5

  • ISSN

  • e-ISSN

  • Number of pages

    28

  • Pages from-to

    26716-26743

  • Publisher name

  • Place of publication

  • Event location

    Vienna, Austria

  • Event date

    Jan 1, 2026

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article