2 citations · 3 across the 5 of their papers we have counts for
7 papers
MGDoc: Pre-training with Multi-granular Hierarchy for Document Image Understanding
Zilong Wang, Jiuxiang Gu, Chris Tensmeyer +5
Document images are a ubiquitous source of data where the text is organized in a complex hierarchical structure ranging from fine granularity (e.g., words), medium granularity (e.g…
Towards Few-shot Entity Recognition in Document Images: A Label-aware Sequence-to-Sequence Framework
Zilong Wang, Jingbo Shang
Entity recognition is a fundamental task in understanding document images. Traditional sequence labeling frameworks treat the entity types as class IDs and rely on extensive data a…
LayoutReader: Pre-training of Text and Layout for Reading Order Detection
Zilong Wang, Yiheng Xu, Lei Cui +2
Reading order detection is the cornerstone to understanding visually-rich documents (e.g., receipts and forms). Unfortunately, no existing work took advantage of advanced deep lear…
GroupLink: An End-to-end Multitask Method for Word Grouping and Relation Extraction in Form Understanding
Zilong Wang, Mingjie Zhan, Houxing Ren +4
Forms are a common type of document in real life and carry rich information through textual contents and the organizational structure. To realize automatic processing of forms, wor…
DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding
Zilong Wang, Mingjie Zhan, Xuebo Liu +1
Form understanding depends on both textual contents and organizational structure. Although modern OCR performs well, it is still challenging to realize general form understanding b…
Exploring Semantic Capacity of Terms
Jie Huang, Zilong Wang, Kevin Chen-Chuan Chang +2
We introduce and study semantic capacity of terms. For example, the semantic capacity of artificial intelligence is higher than that of linear regression since artificial intellige…