Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs,
and various other document types, a flurry of table pre-training frameworks have been …

Tables are everywhere, from scientific journals, articles, websites, and newspapers all the
way to items we buy at the supermarket. Detecting them is thus of utmost importance to …

We propose TUTA, a unified pre-training architecture for understanding generally structured
tables. Noticing that understanding a table requires spatial, hierarchical, and semantic …

Tables contain a significant portion of the world's structured information. The ability to
efficiently and accurately understand, process, reason about, analyze, and generate tabular …

Tabular data is a way to structure, organize, and present information conveniently and
effectively. Real-world tables present data in two dimensions by arranging cells in matrices …

Tables are probably the most natural way to represent relational data in various media and
formats. They store a large number of valuable facts that could be utilized for question …

Tables store rich numerical data, but numerical reasoning over tables is still a challenge. In
this paper, we find that the spreadsheet formula, which performs calculations on numerical …

Tables are widely used for data storage and presentation due to their high flexibility in
layout. The importance of tables as information carriers and the complexity of tabular data …

Table is a widely used data form in webpages, spreadsheets, or PDFs to organize and
present structural data. Although studies on table structure recognition have been …

Document parsing is essential for converting unstructured and semi-structured documents-
such as contracts, academic papers, and invoices-into structured, machine-readable data …