PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering

arXiv:2404.12720v1 Announce Type: new
Abstract: Document Question Answering (QA) presents a challenge in understanding visually-rich documents (VRD), particularly those dominated by lengthy textual content like research journal articles. Existing studies primarily focus on real-world documents with sparse text, while challenges persist in comprehending the hierarchical semantic relations among multiple pages to locate multimodal components. To address this gap, we propose PDF-MVQA, which is tailored for research journal articles, encompassing multiple pages and multimodal information retrieval. Unlike traditional machine reading comprehension …

abstract articles arxiv challenge challenges cs.cl cs.cv dataset document documents focus hierarchical information journal multimodal pdf question question answering relations research retrieval semantic studies text textual type understanding visual world