@inproceedings{morillo-etal-2025-verbanexai,
    title = "{V}erba{N}ex{AI} at {S}em{E}val-2025 Task 3: Fact Retrieval with {G}oogle Snippets for {LLM} Context Filtering to identify Hallucinations",
    author = "Morillo, Anderson  and
      Puertas, Edwin  and
      Martinez Santos, Juan Carlos",
    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-1.202/",
    pages = "1534--1541",
    ISBN = "979-8-89176-273-2",
    abstract = "Thefirst approach leverages advanced LLMs, employing a chain-of-thought prompting strategywith one-shot learning and Google snippets forcontext retrieval, demonstrating superior performance. The second approach utilizes traditional NLP analysis techniques, including semantic ranking, token-level extraction, and rigorous data cleaning, to identify hallucinations"
}