@inproceedings{abdallah-el-beltagy-2025-hallusearch,
    title = "{H}allu{S}earch at {S}em{E}val-2025 Task 3: A Search-Enhanced {RAG} Pipeline for Hallucination Detection",
    author = "Abdallah, Mohamed  and
      El - Beltagy, Samhaa",
    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-1.189/",
    pages = "1436--1441",
    ISBN = "979-8-89176-273-2",
    abstract = "We present HalluSearch, a multilingual pipeline designed to detect fabricated text spans in Large Language Model (LLM) outputs as part of Mu-SHROOM. HalluSearch couples retrieval-augmented verification with fine-grained factual splitting to identify and localize hallucinations in 14 different languages. Empirical evaluations show that HalluSearch performs competitively, placing fourth in both English (within the top 10{\%}) and Czech. While the system{'}s retrieval-based strategy generally proves robust, it faces challenges in languages with limited online coverage, underscoring the need for further research to ensure consistent hallucination detection across diverse linguistic contexts."
}