Workshop on Document Intelligence Understanding
Soyeon Caren Han Yihao Ding Siwen Luo Josiah Poon HeeGuen Yoon Zhe Huang Paul Duuring Eun Jung Holden
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.