@inproceedings{chernyshevich-2025-core,
    title = "Core Intelligence at {S}em{E}val-2025 Task 8: Multi-hop {LLM} Agent for Tabular Question Answering",
    author = "Chernyshevich, Maryna",
    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/transition-to-people-yaml/2025.semeval-1.174/",
    pages = "1313--1317",
    ISBN = "979-8-89176-273-2",
    abstract = "This paper describes a multi-hop LLM agent for tabular question answering developed for SemEval-2025 Task 8 and ranked 6th with 87{\%} accuracy. Our approach combines proprietary LLM (ChatGPT-3.5-turbo) for code generation and open source LLM (Llama-3.2-3B) for answer validation."
}