AI RESEARCH

Lightweight and Production-Ready PDF Visual Element Parsing

arXiv CS.CV

ArXi:2604.23276v1 Announce Type: new PDF documents contain critical visual elements such as figures, tables, and forms whose accurate extraction is essential for document understanding and multimodal retrieval-augmented generation (RAG). Existing PDF parsers often miss complex visuals, extract non-informative artifacts (e.g., watermarks, logos), produce fragmented elements, and fail to reliably associate captions with their corresponding elements, which degrades downstream retrieval and question answering.