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    <abstract>Fact-checking is essential due to the explosion of misinformation in the media ecosystem. Although false information exists in every language and country, most research to solve the problem has mainly concentrated on huge communities like English and Chinese. Low-resource languages like Vietnamese are necessary to explore corpora and models for fact verification. To bridge this gap, we construct ViWikiFC, the first manually annotated open-domain corpus for Vietnamese Wikipedia Fact Checking more than 20K claims generated by converting evidence sentences extracted from Wikipedia articles. We analyze our corpus through many linguistic aspects, from the new dependency rate, the new n-gram rate, and the new word rate. We conducted various experiments for Vietnamese fact-checking, including evidence retrieval and verdict prediction. BM25 and InfoXLM_Large achieved the best results in two tasks, with BM25 achieving an accuracy of 88.30% for SUPPORTS, 86.93% for REFUTES, and only 56.67% for the NEI label in the evidence retrieval task. InfoXLM_Large achieved an F₁ score of 86.51%. Furthermore, we also conducted a pipeline approach, which only achieved a strict accuracy of 67.00% when using InfoXLM_Large and BM25. These results demonstrate that our dataset is challenging for the Vietnamese language model in fact-checking tasks.</abstract>
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%0 Conference Proceedings
%T ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source
%A Le, Hung Tuan
%A To, Long Truong
%A Nguyen, Manh Trong
%A Nguyen, Kiet Van
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F le-etal-2026-viwikifc
%X Fact-checking is essential due to the explosion of misinformation in the media ecosystem. Although false information exists in every language and country, most research to solve the problem has mainly concentrated on huge communities like English and Chinese. Low-resource languages like Vietnamese are necessary to explore corpora and models for fact verification. To bridge this gap, we construct ViWikiFC, the first manually annotated open-domain corpus for Vietnamese Wikipedia Fact Checking more than 20K claims generated by converting evidence sentences extracted from Wikipedia articles. We analyze our corpus through many linguistic aspects, from the new dependency rate, the new n-gram rate, and the new word rate. We conducted various experiments for Vietnamese fact-checking, including evidence retrieval and verdict prediction. BM25 and InfoXLM_Large achieved the best results in two tasks, with BM25 achieving an accuracy of 88.30% for SUPPORTS, 86.93% for REFUTES, and only 56.67% for the NEI label in the evidence retrieval task. InfoXLM_Large achieved an F₁ score of 86.51%. Furthermore, we also conducted a pipeline approach, which only achieved a strict accuracy of 67.00% when using InfoXLM_Large and BM25. These results demonstrate that our dataset is challenging for the Vietnamese language model in fact-checking tasks.
%R 10.63317/5ew98tfds6jc
%U https://aclanthology.org/2026.lrec-1.869/
%U https://doi.org/10.63317/5ew98tfds6jc
%P 11125-11140

Markdown (Informal)

[ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source](https://aclanthology.org/2026.lrec-1.869/) (Le et al., LREC 2026)

• ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source (Le et al., LREC 2026)

ACL

• Hung Tuan Le, Long Truong To, Manh Trong Nguyen, and Kiet Van Nguyen. 2026. ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 11125–11140, Palma de Mallorca, Spain. ELRA Language Resource Association.