@inproceedings{drinkall-etal-2025-forecasting,
    title = "Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative {LLM}s",
    author = "Drinkall, Felix  and
      Pierrehumbert, Janet B.  and
      Zohren, Stefan",
    editor = "Chen, Chung-Chi  and
      Moreno-Sandoval, Antonio  and
      Huang, Jimin  and
      Xie, Qianqian  and
      Ananiadou, Sophia  and
      Chen, Hsin-Hsi",
    booktitle = "Proceedings of the Joint Workshop of the 9th Financial Technology and Natural Language Processing (FinNLP), the 6th Financial Narrative Processing (FNP), and the 1st Workshop on Large Language Models for Finance and Legal (LLMFinLegal)",
    month = jan,
    year = "2025",
    address = "Abu Dhabi, UAE",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2025.finnlp-1.11/",
    pages = "118--133"
}