@inproceedings{ratnakar-etal-2026-one,
    title = "One Retrieval to Cover Them All: Co-occurrence-Aware Knowledge Base Reorganization for Session-Level {RAG}",
    author = "Ratnakar, Shivam  and
      Zhu, Yixuan  and
      Cheng, Cecilia  and
      Vijayakumar, Chaya",
    editor = "Chen, Canyu  and
      Zhang, Yuji  and
      Li, Zoey Sha  and
      Wang, Zihan  and
      Wang, Qineng  and
      Su, Jinyan  and
      Kargupta, Priyanka  and
      Marjanovi{\'c}, Sara Vera  and
      Pan, Jeff Z.  and
      Bansal, Mohit  and
      Augenstein, Isabelle  and
      Han, Jiawei  and
      Ji, Heng  and
      Li, Manling",
    booktitle = "Proceedings of the 4th Workshop on Towards Knowledgeable Foundation Models ({K}now{FM} 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.knowfm-1.14/",
    pages = "173--182",
    ISBN = "979-8-89176-403-3",
    abstract = "RAG systems retrieve documents optimized for answering *one query at a time*. Yet enterprise users arrive with *sessions*, that is, coherent episodes of related questions that span semantically distant parts of the knowledge base. We show that a single retrieval call over a standard knowledge base covers only 41{\%} of a user{'}s session-level information need. To close this gap, we reorganize the KB offline using co-occurrence-aware clustering and expand retrieval candidates through cluster neighborhoods at query time. On WixQA (6,221 enterprise support articles), our method raises single-query session coverage to 58{\%} (+17{\%} absolute; 95{\%} CI: [14.1, 20.4]), reduces retrieval calls to 70{\%} coverage by 34{\%}, and compresses the KB to 20{\%} of its original size, all consistently across four embedding models and six functional domains. We argue that session-level coverage, not single-query recall, should be the primary metric for enterprise RAG evaluation."
}