Structured text understanding on Visually Rich Documents (VRDs) is a crucial part of
Document Intelligence. Due to the complexity of content and layout in VRDs, structured text …

As organizations increasingly rely on diverse data sources like invoices and surveys,
efficient Information Extraction (IE) is crucial. Natural Language Processing (NLP) enhances …

We propose a novel end-to-end document understanding model called SeRum (SElective
Region Understanding Model) for extracting meaningful information from document images …

Recent grid-based document representations like BERTgrid allow the simultaneous
encoding of the textual and layout information of a document in a 2D feature map so that …

Understanding document images (eg, invoices) has been an important research topic and
has many applications in document processing automation. Through the latest advances in …

This paper focuses on solving Document Information Extraction (DIE) in the wild problem,
which is rarely explored before. In contrast to existing studies mainly tailored for document …

The output structure of database-like tables, consisting of values structured in horizontal
rows and vertical columns identifiable by name, can cover a wide range of NLP tasks …

Extracting key information from documents represents a large portion of business workloads
and therefore offers a high potential for efficiency improvements and process automation …

Abstract Transformer-based Language Models are widely used in Natural Language
Processing related tasks. Thanks to their pre-training, they have been successfully adapted …

The importance of automated document understanding in terms of today's businesses'
speed, efficiency, and cost reduction is indisputable. Although structured and semi …