Machine learning (ML) on tabular data is ubiquitous, yet obtaining abundant high-quality
tabular data for model training remains a significant obstacle. Numerous works have …

As an important component of data exploration and integration, Column Type Annotation
(CTA) aims to label columns of a table with one or more semantic types. With the recent …

Detecting semantic types of columns in data lake tables is an important application. A key
bottleneck in semantic type detection is the availability of human annotation due to the …

The attention to table understanding using recent natural language models has been
growing. However, most related works tend to focus on learning the structure of the table …

Long-form text matching plays a significant role in many real world Natural Language
processing (NLP) and Information Retrieval (IR) applications. Recently Transformer based …

Data lakes are massive collections of structured and unstructured datasets. While these
collections consist of various data formats, we focus on tabular data in data lakes. With the …