@inproceedings{wang-etal-2026-rethinking,
    title = "Rethinking Reading Order: Toward Generalizable Document Understanding with {LLM}-based Relation Modeling",
    author = "Wang, Weishi  and
      Hu, Hengchang  and
      Dahlmeier, Daniel",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.eacl-long.192/",
    pages = "4110--4130",
    ISBN = "979-8-89176-380-7",
    abstract = "Document understanding requires modeling both structural and semantic relationships between the layout elements within the document, with human-perceived reading order (RO) playing a crucial yet often neglected role compared to heuristic OCR sequences used by most existing models. Previous approaches depend on costly, inconsistent human annotations, limiting scalability and generalization. To bridge the gap, we propose a cost-effective paradigm that leverages large language models (LLMs) to infer global RO and inter-element layout relations without human supervision. By explicitly incorporating RO as structural guidance, our method captures hierarchical, document-level dependencies beyond local adjacency. Experiments on Semantic Entity Recognition, Entity Linking, and Document Question Answering show consistent improvements over baseline methods. Notably, LLM-inferred RO, even when differing from ground-truth adjacency, provides richer global structural priors and yields superior downstream performance. These results and findings demonstrate the scalability and significance of RO-aware modeling, advancing both LLMs and lightweight layout-aware models for robust document understanding. Code, data, and more details will be made publicly available after corporate review, in accordance with SAP{'}s corporate open-source policy."
}