2 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding
Chong Zhang, Yi Tu, Yixi Zhao +8
Modeling and leveraging layout reading order in visually-rich documents (VrDs) is critical in document intelligence as it captures the rich structure semantics within documents. Pr…
UNER: A Unified Prediction Head for Named Entity Recognition in Visually-rich Documents
Yi Tu, Chong Zhang, Ya Guo +4
The recognition of named entities in visually-rich documents (VrD-NER) plays a critical role in various real-world scenarios and applications. However, the research in VrD-NER face…
Unveiling the Deficiencies of Pre-trained Text-and-Layout Models in Real-world Visually-rich Document Information Extraction
Chong Zhang, Yixi Zhao, Yulu Xie +7
Recently developed pre-trained text-and-layout models (PTLMs) have shown remarkable success in multiple information extraction tasks on visually-rich documents (VrDs). However, des…
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
Chong Zhang, Ya Guo, Yi Tu +5
Recent advances in multimodal pre-trained models have significantly improved information extraction from visually-rich documents (VrDs), in which named entity recognition (NER) is…
Universal Multi-modal Entity Alignment via Iteratively Fusing Modality Similarity Paths
Bolin Zhu, Xiaoze Liu, Xin Mao +4
The objective of Entity Alignment (EA) is to identify equivalent entity pairs from multiple Knowledge Graphs (KGs) and create a more comprehensive and unified KG. The majority of E…