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        <title>Team Cantharellus at SemEval-2025 Task 3: Hallucination Span Detection with Fine Tuning on Weakly Supervised Synthetic Data</title>
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    <abstract>This paper describes our submission to SemEval-2025 Task-3: Mu-SHROOM, the Multilingual Shared-task on Hallucinations and Related Observable Overgeneration Mistakes, which mainly aims at detecting spans of LLM-generated text corresponding to hallucinations in multilingual and multi-model context. We explored an approach of fine-tuning pretrained language models available on Hugging Face. The results show that predictions made by a pretrained model fine-tuned on synthetic data achieve a relatively high degree of alignment with human-generated labels. We participated in 13 out of 14 available languages and reached an average ranking of 10th out of 41 participating teams, with our highest ranking reaching the top 5 place.</abstract>
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%0 Conference Proceedings
%T Team Cantharellus at SemEval-2025 Task 3: Hallucination Span Detection with Fine Tuning on Weakly Supervised Synthetic Data
%A Mo, Xinyuan
%A Vorontsov, Nikolay
%A Zang, Tiankai
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F mo-etal-2025-team
%X This paper describes our submission to SemEval-2025 Task-3: Mu-SHROOM, the Multilingual Shared-task on Hallucinations and Related Observable Overgeneration Mistakes, which mainly aims at detecting spans of LLM-generated text corresponding to hallucinations in multilingual and multi-model context. We explored an approach of fine-tuning pretrained language models available on Hugging Face. The results show that predictions made by a pretrained model fine-tuned on synthetic data achieve a relatively high degree of alignment with human-generated labels. We participated in 13 out of 14 available languages and reached an average ranking of 10th out of 41 participating teams, with our highest ranking reaching the top 5 place.
%U https://aclanthology.org/2025.semeval-1.226/
%P 1724-1736

Markdown (Informal)

[Team Cantharellus at SemEval-2025 Task 3: Hallucination Span Detection with Fine Tuning on Weakly Supervised Synthetic Data](https://aclanthology.org/2025.semeval-1.226/) (Mo et al., SemEval 2025)

• Team Cantharellus at SemEval-2025 Task 3: Hallucination Span Detection with Fine Tuning on Weakly Supervised Synthetic Data (Mo et al., SemEval 2025)

ACL

• Xinyuan Mo, Nikolay Vorontsov, and Tiankai Zang. 2025. Team Cantharellus at SemEval-2025 Task 3: Hallucination Span Detection with Fine Tuning on Weakly Supervised Synthetic Data. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 1724–1736, Vienna, Austria. Association for Computational Linguistics.