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        <title>The UNLP 2024 Shared Task on Fine-Tuning Large Language Models for Ukrainian</title>
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    <name type="personal">
        <namePart type="given">Mariana</namePart>
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        <namePart type="given">Oleksiy</namePart>
        <namePart type="family">Syvokon</namePart>
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            <title>Proceedings of the Third Ukrainian Natural Language Processing Workshop (UNLP) @ LREC-COLING 2024</title>
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            <namePart type="given">Mariana</namePart>
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        <name type="personal">
            <namePart type="given">Nataliia</namePart>
            <namePart type="family">Romanyshyn</namePart>
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        <name type="personal">
            <namePart type="given">Andrii</namePart>
            <namePart type="family">Hlybovets</namePart>
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            <namePart type="given">Oleksii</namePart>
            <namePart type="family">Ignatenko</namePart>
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    <abstract>This paper presents the results of the UNLP 2024 shared task, the first Shared Task on Fine-Tuning Large Language Models for the Ukrainian language. The goal of the task was to facilitate the creation of models that have knowledge of the Ukrainian language, history, and culture, as well as common knowledge, and are capable of generating fluent and accurate responses in Ukrainian. The participants were required to use models with open weights and reasonable size to ensure the reproducibility of the solutions. The participating systems were evaluated using multiple-choice exam questions and manually crafted open questions. Three teams submitted their solutions before the deadline, and two teams submitted papers that were accepted to appear in the UNLP workshop proceedings and are referred to in this report. The Codabench leaderboard is left open for further submissions.</abstract>
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%0 Conference Proceedings
%T The UNLP 2024 Shared Task on Fine-Tuning Large Language Models for Ukrainian
%A Romanyshyn, Mariana
%A Syvokon, Oleksiy
%A Kyslyi, Roman
%Y Romanyshyn, Mariana
%Y Romanyshyn, Nataliia
%Y Hlybovets, Andrii
%Y Ignatenko, Oleksii
%S Proceedings of the Third Ukrainian Natural Language Processing Workshop (UNLP) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F romanyshyn-etal-2024-unlp
%X This paper presents the results of the UNLP 2024 shared task, the first Shared Task on Fine-Tuning Large Language Models for the Ukrainian language. The goal of the task was to facilitate the creation of models that have knowledge of the Ukrainian language, history, and culture, as well as common knowledge, and are capable of generating fluent and accurate responses in Ukrainian. The participants were required to use models with open weights and reasonable size to ensure the reproducibility of the solutions. The participating systems were evaluated using multiple-choice exam questions and manually crafted open questions. Three teams submitted their solutions before the deadline, and two teams submitted papers that were accepted to appear in the UNLP workshop proceedings and are referred to in this report. The Codabench leaderboard is left open for further submissions.
%U https://aclanthology.org/2024.unlp-1.9
%P 67-74

Markdown (Informal)

[The UNLP 2024 Shared Task on Fine-Tuning Large Language Models for Ukrainian](https://aclanthology.org/2024.unlp-1.9) (Romanyshyn et al., UNLP 2024)

• The UNLP 2024 Shared Task on Fine-Tuning Large Language Models for Ukrainian (Romanyshyn et al., UNLP 2024)

ACL

• Mariana Romanyshyn, Oleksiy Syvokon, and Roman Kyslyi. 2024. The UNLP 2024 Shared Task on Fine-Tuning Large Language Models for Ukrainian. In Proceedings of the Third Ukrainian Natural Language Processing Workshop (UNLP) @ LREC-COLING 2024, pages 67–74, Torino, Italia. ELRA and ICCL.