Data collection is a major bottleneck in machine learning and an active research topic in
multiple communities. There are largely two reasons data collection has recently become a …

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 …

Data preparation is widely recognized as the most time-consuming process in modern
business intelligence (BI) and machine learning (ML) projects. Automating complex data …

The recent Programming By Example (PBE) techniques such as FlashFill have shown great
promise for enabling end-users to perform data transformation tasks using input-output …

In 2008, we wrote about WebTables, an effort to exploit the large and diverse set of
structured databases casually published online in the form of HTML tables. The past decade …

Data errors are ubiquitous in tables. Extensive research in this area has resulted in a rich
variety of techniques, each often targeting a specific type of errors, eg, numeric outliers …

CSV is a popular Open Data format widely used in a variety of domains for its simplicity and
effectiveness in storing and disseminating data. Unfortunately, data published in this format …

Traditional equi-join relies solely on string equality comparisons to perform joins. However,
in scenarios such as ad-hoc data analysis in spreadsheets, users increasingly need to join …

Given a single column of values, existing approaches typically employ regex-like rules to
detect errors by finding anomalous values inconsistent with others. Such techniques make …

Tables in documents are a widely-available and rich source of information, but not yet well-
utilised computationally because of the difficulty in automatically extracting their structure …