We present TNCR, a new table dataset with varying image quality collected from open
access websites. TNCR dataset can be used for table detection in scanned document …

Global supply chains are kept viable through the information shared through billions of
electronic documents, many of which extensively use tables to display critical information …

Several studies have focused on incorporating language models with entity descriptions to
facilitate the model with a better understanding of knowledge. Existing methods usually …

Industry benchmarking involves comparing and analyzing a company's performance with
other top-performing enterprises. PDF documents contain valuable corporate information …

Billions of documents in data sheet format are shared between various organizations across
the globe on a daily basis. The essential information in these documents is presented in …

Tabular data in digital documents is widely used to express compact and important
information for readers. However, it is challenging to parse tables from unstructured digital …

Table Detection has become a fundamental task for visually rich document understanding
with the surging number of electronic documents. However, popular public datasets widely …

Abstract Numerical Table-Text Question Answering aims to predict the program over
heterogeneous tabular and textual information, which has recently attracted strong attention …

In academic institutions, processing and evaluating documents such as exam scripts
remains a labor-intensive process susceptible to human error. Traditional digitization …

Table Structure Recognition (TSR) is pivotal in document analysis, especially in end-to-end
automated identification, which profoundly impacts decision-making and efficiency spanning …