Abstract Information extraction plays an important role for data transformation in business
cases. However, building extraction systems in actual cases face two challenges:(i) the …

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

This paper presents a practical approach to fine-grained information extraction. Through
plenty of authors' experiences in practically applying information extraction to business …

Extracting information from documents usually relies on natural language processing
methods working on one-dimensional sequences of text. In some cases, for example, for the …

Document information extraction tasks performed by humans create data consisting of a
PDF or document image input, and extracted string outputs. This end-to-end data is naturally …

The present paper is focused on information extraction from key fields of invoices using two
different methods based on sequence labeling. Invoices are semi-structured documents in …

Abstract Information extraction from semi-structured documents is crucial for frictionless
business-to-business (B2B) communication. While machine learning problems related to …

This article focuses on information extraction in historical handwritten marriage records.
Traditional approaches rely on a sequential pipeline of two consecutive tasks: handwriting …

Techniques for automatically extracting important content elements from business
documents such as contracts, statements, and filings have the potential to make business …

This paper proposes two natural language processing models for extracting useful
information from multilingual, unstructured (free form) CV documents. The model identifies …