Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is
nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or …

Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary
input modality to direct manipulation for visual analytics can provide an engaging user …

Relational tables on the Web store a vast amount of knowledge. Owing to the wealth of such
tables, there has been tremendous progress on a variety of tasks in the area of table …

Existing work on tabular representation learning jointly models tables and associated text
using self-supervised objective functions derived from pretrained language models such as …

Deep learning based techniques have been recently used with promising results for data
integration problems. Some methods directly use pre-trained embeddings that were trained …

Natural language interfaces (NLls) have shown great promise for visual data analysis,
allowing people to flexibly specify and interact with visualizations. However, developing …

Inferring meta information about tables, such as column headers or relationships between
columns, is an active research topic in data management as we find many tables are …

Tabular data often refers to data that is organized in a table with rows and columns. We
observe that this data format is widely used on the Web and within enterprise data …

Detecting the semantic types of data columns in relational tables is important for various
data preparation and information retrieval tasks such as data cleaning, schema matching …

Language models, such as GPT-3.5 and ChatGPT, demonstrate remarkable abilities to
follow diverse human instructions and perform a wide range of tasks. However, when …