{
 "id": "MultiMind-SemEval2025/Augmented_MultiClaim_FactCheck_Retrieval",
 "owner": "MultiMind-SemEval2025",
 "name": "Augmented_MultiClaim_FactCheck_Retrieval",
 "downloads": 113,
 "likes": 1,
 "last_modified": "2025-08-08T14:53:36.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
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 "citation": "@inproceedings{abootorabi-etal-2025-multimind,\n    title = \"{M}ulti{M}ind at {S}em{E}val-2025 Task 7: Crosslingual Fact-Checked Claim Retrieval via Multi-Source Alignment\",\n    author = \"Abootorabi, Mohammad Mahdi  and\n      Ghahramani Kure, Alireza  and\n      Mohammadkhani, Mohammadali  and\n      Elahimanesh, Sina  and\n      Ali Panah, Mohammad Ali\",\n    editor = \"Rosenthal, Sara  and\n      Ros{\\'a}, Aiala  and\n      Ghosh, Debanjan  and\n      Zampieri, Marcos\",\n    booktitle = \"Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)\",\n    month = jul,\n    year = \"2025\",\n    address = \"Vienna, Austria\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2025.semeval-1.303/\",\n    pages = \"2325--2335\",\n    ISBN = \"979-8-89176-273-2\",\n    abstract = \"This paper presents our system for SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval. In an era where misinformation spreads rapidly, effective fact-checking is increasingly critical. We introduce {\\{}textbf{\\{}TriAligner{\\}}{\\}}, a novel approach that leverages a dual-encoder architecture with contrastive learning and incorporates both native and English translations across different modalities. Our method effectively retrieves claims across multiple languages by learning the relative importance of different sources in alignment. To enhance robustness, we employ efficient data preprocessing and augmentation using large language",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "af2cd1d642eaf7ae845586e7e0e595b55b8741db",
 "stated_evidence": "https://huggingface.co/datasets/MultiMind-SemEval2025/Augmented_MultiClaim_FactCheck_Retrieval/blob/af2cd1d642eaf7ae845586e7e0e595b55b8741db/README.md",
 "file_evidence": "https://huggingface.co/datasets/MultiMind-SemEval2025/Augmented_MultiClaim_FactCheck_Retrieval/tree/af2cd1d642eaf7ae845586e7e0e595b55b8741db",
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}