@inproceedings{olawore-etal-2025-optimizing,
    title = "Optimizing {RAG}: Classifying Queries for Dynamic Processing",
    author = "Olawore, Kabir  and
      McTear, Michael  and
      Bi, Yaxin  and
      Griol, David",
    editor = "Torres, Maria Ines  and
      Matsuda, Yuki  and
      Callejas, Zoraida  and
      del Pozo, Arantza  and
      D'Haro, Luis Fernando",
    booktitle = "Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology",
    month = may,
    year = "2025",
    address = "Bilbao, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.iwsds-1.14/",
    pages = "160--164",
    ISBN = "979-8-89176-248-0",
    abstract = "In Retrieval-Augmented Generation (RAG) systems efficient information retrieval is crucial for enhancing user experience and satisfaction, as response times and computational demands significantly impact performance. RAG can be unnecessarily resource-intensive for frequently asked questions (FAQs) and simple questions. In this paper we introduce an approach in which we categorize user questions into simple queries that do not require RAG processing. Evaluation results show that our proposal reduces latency and improves response efficiency compared to systems relying solely on RAG."
}