Tables, typically two-dimensional and structured to store large amounts of data, are
essential in daily activities like database queries, spreadsheet manipulations, Web table …

Recent breakthroughs in large language modeling have facilitated rigorous exploration of
their application in diverse tasks related to tabular data modeling, such as prediction, tabular …

Interpretable machine learning has exploded as an area of interest over the last decade,
sparked by the rise of increasingly large datasets and deep neural networks …

Semi-structured tables are ubiquitous. There has been a variety of tasks that aim to
automatically interpret, augment, and query tables. Current methods often require …

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 …

In the financial industry, credit scoring is a fundamental element, shaping access to credit
and determining the terms of loans for individuals and businesses alike. Traditional credit …

Recently, there has been an increasing interest in extracting and annotating tables on the
Web. This activity allows the transformation of textual data into machine-readable formats to …

This paper explores the utilization of LLMs for data preprocessing (DP), a crucial step in the
data mining pipeline that transforms raw data into a clean format. We instruction-tune local …

While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …

Spreadsheet manipulation is widely-existing in most daily works and significantly improves
the working efficiency. Large language model (LLM) has been recently attempted for …