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

In the last few years, the natural language processing community has witnessed advances
in neural representations of free texts with transformer-based language models (LMs). Given …

Data management is indispensable for informed decision-making in the big data era. In the
meantime, Large Language Models (LLMs), equipped with billions of model parameters and …

Large language models (LLMs) are becoming attractive as few-shot reasoners to solve
Natural Language (NL)-related tasks. However, there is still much to learn about how well …

Recently, the topic of table pre-training has attracted considerable research interest.
However, how to employ table pre-training to boost the performance of tabular prediction …

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 …

Recent development of deep neural networks (DNNs) for tabular learning has largely
benefited from the capability of DNNs for automatic feature interaction. However, the …

In this work, we share our experience on tele-knowledge pre-training for fault analysis, a
crucial task in telecommunication applications that requires a wide range of knowledge …

Logical table-to-text generation is a task that involves generating logically faithful sentences
from tables, which requires models to derive logical level facts from table records via logical …

Language models and specialized table embedding models have recently demonstrated
strong performance on many tasks over tabular data. Researchers and practitioners are …