Publication result detail

BenCzechMark : A Czech-Centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism

FAJČÍK, M.; DOČEKAL, M.; DOLEŽAL, J.; ONDŘEJ, K.; BENEŠ, K.; SMRŽ, P.; POLOK, A.; HRADIŠ, M.

Original Title

BenCzechMark : A Czech-Centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism

English Title

BenCzechMark : A Czech-Centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism

Type

Scopus Article

Original Abstract

We present BenCzechMark (BCM), the first comprehensive Czech language benchmark designed for large language models, offering diverse tasks, multiple task formats, and multiple evaluation metrics. Its duel scoring system is grounded in statistical significance theory and uses aggregation across tasks inspired by social preference theory. Our benchmark encompasses 50 challenging tasks, with corresponding test datasets, primarily in native Czech, with 14 newly collected ones. These tasks span 8 categories and cover diverse domains, including historical Czech news, essays from pupils or language learners, and spoken word. Furthermore, we collect and clean BUT-Large Czech Collection, the largest publicly available clean Czech language corpus, and use it for (i) contamination analysis and (ii) continuous pretraining of the first Czech-centric 7B language model with Czech-specific tokenization. We use our model as a baseline for comparison with publicly available multilingual models. Lastly, we release and maintain a leaderboard with existing 50 model submissions, where new model submissions can be made at https://huggingface.co/spaces/CZLC/BenCzechMark.

English abstract

We present BenCzechMark (BCM), the first comprehensive Czech language benchmark designed for large language models, offering diverse tasks, multiple task formats, and multiple evaluation metrics. Its duel scoring system is grounded in statistical significance theory and uses aggregation across tasks inspired by social preference theory. Our benchmark encompasses 50 challenging tasks, with corresponding test datasets, primarily in native Czech, with 14 newly collected ones. These tasks span 8 categories and cover diverse domains, including historical Czech news, essays from pupils or language learners, and spoken word. Furthermore, we collect and clean BUT-Large Czech Collection, the largest publicly available clean Czech language corpus, and use it for (i) contamination analysis and (ii) continuous pretraining of the first Czech-centric 7B language model with Czech-specific tokenization. We use our model as a baseline for comparison with publicly available multilingual models. Lastly, we release and maintain a leaderboard with existing 50 model submissions, where new model submissions can be made at https://huggingface.co/spaces/CZLC/BenCzechMark.

Authors

FAJČÍK, M.; DOČEKAL, M.; DOLEŽAL, J.; ONDŘEJ, K.; BENEŠ, K.; SMRŽ, P.; POLOK, A.; HRADIŠ, M.

Released

02.09.2025

Periodical

Transactions of the Association for Computational Linguistics

Volume

13

Number

9

State

United States of America

Pages from

1068

Pages to

1095

Pages count

28

URL

BibTex

@article{BUT198824,
  author="Martin {Fajčík} and Martin {Dočekal} and Jan {Doležal} and Karel {Ondřej} and Karel {Beneš} and Pavel {Smrž} and Alexander {Polok} and Michal {Hradiš}",
  title="BenCzechMark : A Czech-Centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism",
  journal="Transactions of the Association for Computational Linguistics",
  year="2025",
  volume="13",
  number="9",
  pages="1068--1095",
  doi="10.1162/TACL.a.32",
  url="https://direct.mit.edu/tacl/article/doi/10.1162/TACL.a.32/132962/BenCzechMark-A-Czech-Centric-Multitask-and"
}

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