This paper introduces a new information extraction model for business documents. Different
from prior studies which only base on span extraction or sequence labeling, the model takes …

Abstract Information extraction (IE) is a vital step of digitization that reduces paperwork in
offices. However, the adaptation of common IE systems to actual business cases faces two …

Abstract Information extraction (IE) for visually-rich documents (VRDs) has achieved SOTA
performance recently thanks to the adaptation of Transformer-based language models …

We present an empirical study on methods for span finding, the selection of consecutive
tokens in text for some downstream tasks. We focus on approaches that can be employed in …

Information extraction is a key corner-stone in the digitization of office data which requires
the conversion of unstructured to structured data. However, in the actual application to …

Information Extraction refers to a collection of tasks within Natural Language Processing
(NLP) that identifies sub-sequences within text and their labels. These tasks have been used …

Span extraction, aiming to extract text spans (such as words or phrases) from plain texts, is a
fundamental process in Information Extraction. Recent works introduce the label knowledge …

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 …

Information extraction is a well-known topic that plays a critical role in many NLP
applications as its outputs can be considered as an entrance step for digital transformation …

Like for many text understanding and generation tasks, pre-trained languages models have
emerged as a powerful approach for extracting information from business documents …