@inproceedings{ueda-etal-2026-scan,
    title = "{SCAN}: Semantic Document Layout Analysis for Textual and Visual Retrieval-Augmented Generation",
    author = "Ueda, Nobuhiro  and
      Dong, Yuyang  and
      Boros, Kriszti{\'a}n  and
      Ito, Daiki  and
      Sera, Takuya  and
      Oyamada, Masafumi",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EACL} 2026",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.findings-eacl.82/",
    pages = "1618--1637",
    ISBN = "979-8-89176-386-9",
    abstract = "With the increasing adoption of Large Language Models (LLMs) and Vision-Language Models (VLMs),rich document analysis technologies for applications like Retrieval-Augmented Generation (RAG)and visual RAG are gaining significant attention.Recent research indicates that using VLMs yields better RAG performance,but processing rich documents remains a challenge since a single page contains large amounts of information.In this paper, we present SCAN (SemantiC Document Layout ANalysis),a novel approach that enhances both textual and visual Retrieval-Augmented Generation (RAG) systemsthat work with visually rich documents.It is a VLM-friendly approach that identifies document components with appropriate semantic granularity,balancing context preservation with processing efficiency.SCAN uses a coarse-grained semantic approach that divides documents into coherent regions covering contiguous components.We trained the SCAN model by fine-tuning object detection models on an annotated dataset.Our experimental results across English and Japanese datasets demonstrate that applying SCAN improvesend-to-end textual RAG performance by up to 9.4 points and visual RAG performance by up to 10.4 points,outperforming conventional approaches and even commercial document processing solutions."
}