Document understanding and information extraction include different tasks to
understand a document and extract valuable information automatically. Recently,
there has been a rising demand for developing document understanding among
different domains, including business, law, and medicine, to boost the
efficiency of work that is associated with a large number of documents. This
workshop aims to bring together researchers and industry developers in the
field of document intelligence and understanding diverse document types to
boost automatic document processing and understanding techniques. We also
released a data challenge on the recently introduced document-level VQA
dataset, PDFVQA. The PDFVQA challenge examines the structural and contextual
understandings of proposed models on the natural full document level of
multiple consecutive document pages by including questions with a sequence of
answers extracted from multi-pages of the full document. This task helps to
boost the document understanding step from the single-page level to the full
document level understanding.

文件理解和信息提取是自动理解文档并提取有价值信息的不同任务。该研究聚焦于发展领域包括商业、法律和医学在内的文档理解，以提高大量文档相关工作的效率。此外，该研究还推出了一个数据挑战，针对最近发布的文档级视觉问答（PDFVQA）数据集，旨在促进对自然语言全文档多个连续页面的结构和上下文理解的模型研究。该任务有助于将文档理解从单页水平提升到全文档水平。