@inproceedings{azadi-etal-2025-word2winners,
    title = "Word2winners at {S}em{E}val-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval",
    author = "Azadi, Amirmohammad  and
      Zamani, Sina  and
      Rostamkhani, Mohammadmostafa  and
      Eetemadi, Sauleh",
    editor = "Rosenthal, Sara  and
      Ros{\'a}, Aiala  and
      Ghosh, Debanjan  and
      Zampieri, Marcos",
    booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/corrections-2025-08/2025.semeval-1.182/",
    pages = "1370--1376",
    ISBN = "979-8-89176-273-2",
    abstract = "This paper describes our system for SemEval 2025 Task 7: Previously Fact-Checked Claim Retrieval. The task requires retrieving relevant fact-checks for a given input claim from the extensive, multilingual MultiClaim dataset, which comprises social media posts and fact-checks in several languages. To address this challenge, we first evaluated zero-shot performance using state-of-the-art English and multilingual retrieval models and then fine-tuned the most promising systems, leveraging machine translation to enhance crosslingual retrieval. Our best model achieved an accuracy of 85{\%} on crosslingual data and 92{\%} on monolingual data."
}