12 citations · 50 across the 18 of their papers we have counts for
4 papers · 1 filter
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…
VRDU: A Benchmark for Visually-rich Document Understanding
Zilong Wang, Yichao Zhou, Wei Wei +2
Understanding visually-rich business documents to extract structured data and automate business workflows has been receiving attention both in academia and industry. Although recen…
Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity Recognition
Zihan Wang, Kewen Zhao, Zilong Wang +1
Fine-tuning pre-trained language models has recently become a common practice in building NLP models for various tasks, especially few-shot tasks. We argue that under the few-shot…
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…