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        <title>mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection</title>
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    <name type="personal">
        <namePart type="given">Dominik</namePart>
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            <title>Proceedings of the 20th International Workshop on Semantic Evaluation (2026)</title>
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            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Kochmar</namePart>
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        <name type="personal">
            <namePart type="given">Debanjan</namePart>
            <namePart type="family">Ghosh</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Kai</namePart>
            <namePart type="family">North</namePart>
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        <name type="personal">
            <namePart type="given">Mamoru</namePart>
            <namePart type="family">Komachi</namePart>
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    <abstract>SemEval-2026 Task 10 is focused on conspiracy detection. Specifically, the goal is to detect whether a Reddit comment expresses a conspiracy belief. Our submitted mdok-style system utilizes data augmentation and self-training (to cope with a rather small amount of training data) to finetune the Qwen3-32B model for a binary text-classification task. The submitted system is very competitive, ranking in the 85th percentile (8th out of 52 submissions). The results shown that our approach, which originated in machine-generated text detection, can be used for conspiracy detection as well.</abstract>
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        <url>https://aclanthology.org/2026.semeval-1.64/</url>
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%0 Conference Proceedings
%T mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection
%A Macko, Dominik
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F macko-2026-mdok
%X SemEval-2026 Task 10 is focused on conspiracy detection. Specifically, the goal is to detect whether a Reddit comment expresses a conspiracy belief. Our submitted mdok-style system utilizes data augmentation and self-training (to cope with a rather small amount of training data) to finetune the Qwen3-32B model for a binary text-classification task. The submitted system is very competitive, ranking in the 85th percentile (8th out of 52 submissions). The results shown that our approach, which originated in machine-generated text detection, can be used for conspiracy detection as well.
%U https://aclanthology.org/2026.semeval-1.64/
%P 446-450

Markdown (Informal)

[mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection](https://aclanthology.org/2026.semeval-1.64/) (Macko, SemEval 2026)

• mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection (Macko, SemEval 2026)

ACL

• Dominik Macko. 2026. mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 446–450, San Diego, California, USA. Association for Computational Linguistics.