M3DocDep is an LVLM pipeline that extracts multimodal block embeddings, scores parent-child edges with a biaffine head, decodes a valid dependency tree via MST, and produces section-path-annotated chunks, yielding reported gains of 28-39% on STEDS and 1-15% on nDCG/ANLS.
Is se- mantic chunking worth the computational cost? In Findings of the Association for Computational Lin- guistics: NAACL 2025, pages 2155–2177, Albu- querque, New Mexico, 2025
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M3DocDep: Multi-modal, Multi-page, Multi-document Dependency Chunking with Large Vision-Language Models
M3DocDep is an LVLM pipeline that extracts multimodal block embeddings, scores parent-child edges with a biaffine head, decodes a valid dependency tree via MST, and produces section-path-annotated chunks, yielding reported gains of 28-39% on STEDS and 1-15% on nDCG/ANLS.