16 citations · 22 across the 4 of their papers we have counts for
4 papers
OCR-free Document Understanding Transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim +7
Understanding document images (e.g., invoices) is a core but challenging task since it requires complex functions such as reading text and a holistic understanding of the document.…
Cost-effective End-to-end Information Extraction for Semi-structured Document Images
Wonseok Hwang, Hyunji Lee, Jinyeong Yim +2
A real-world information extraction (IE) system for semi-structured document images often involves a long pipeline of multiple modules, whose complexity dramatically increases its…
Syntactic Question Abstraction and Retrieval for Data-Scarce Semantic Parsing
Wonseok Hwang, Jinyeong Yim, Seunghyun Park +1
Deep learning approaches to semantic parsing require a large amount of labeled data, but annotating complex logical forms is costly. Here, we propose Syntactic Question Abstraction…
Spatial Dependency Parsing for Semi-Structured Document Information Extraction
Wonseok Hwang, Jinyeong Yim, Seunghyun Park +2
Information Extraction (IE) for semi-structured document images is often approached as a sequence tagging problem by classifying each recognized input token into one of the IOB (In…