Workshop on Document Intelligence Understanding
July 31, 2023 Β· Declared Dead Β· π International Conference on Information and Knowledge Management
"No code URL or promise found in abstract"
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Authors
Soyeon Caren Han, Yihao Ding, Siwen Luo, Josiah Poon, HeeGuen Yoon, Zhe Huang, Paul Duuring, Eun Jung Holden
arXiv ID
2307.16369
Category
cs.IR: Information Retrieval
Cross-listed
cs.CV
Citations
1
Venue
International Conference on Information and Knowledge Management
Last Checked
4 months ago
Abstract
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.
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