@inproceedings{yang-etal-2025-ucfe,
    title = "{UCFE}: A User-Centric Financial Expertise Benchmark for Large Language Models",
    author = "Yang, Yuzhe  and
      Zhang, Yifei  and
      Hu, Yan  and
      Guo, Yilin  and
      Gan, Ruoli  and
      He, Yueru  and
      Lei, Mingcong  and
      Zhang, Xiao  and
      Wang, Haining  and
      Xie, Qianqian  and
      Huang, Jimin  and
      Yu, Honghai  and
      Wang, Benyou",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/moar-dois/2025.findings-naacl.300/",
    doi = "10.18653/v1/2025.findings-naacl.300",
    pages = "5429--5448",
    ISBN = "979-8-89176-195-7",
    abstract = "This paper introduces the UCFE: User-Centric Financial Expertise benchmark, an innovative framework designed to evaluate the ability of large language models (LLMs) to handle complex real-world financial tasks. UCFE benchmark adopts a hybrid approach that combines human expert evaluations with dynamic, task-specific interactions to simulate the complexities of evolving financial scenarios. Firstly, we conducted a user study involving 804 participants, collecting their feedback on financial tasks. Secondly, based on this feedback, we created our dataset that encompasses a wide range of user intents and interactions. This dataset serves as the foundation for benchmarking 11 LLMs services using the LLM-as-Judge methodology. Our results show a significant alignment between benchmark scores and human preferences, with a Pearson correlation coefficient of 0.78, confirming the effectiveness of the UCFE dataset and our evaluation approach. UCFE benchmark not only reveals the potential of LLMs in the financial domain but also provides a robust framework for assessing their performance and user satisfaction."
}