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

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 …

In many use-cases, information is stored in text but not available in structured data.
However, extracting data from natural language text to precisely fit a schema, and thus …

Several applications, such as text-to-SQL and computational fact checking, exploit the
relationship between relational data and natural language text. However, state of the art …

Tabular data is becoming increasingly important in Natural Language Processing (NLP)
tasks, such as Tabular Natural Language Inference (TNLI). Given a table and a hypothesis …

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

Declarative querying is one of the main features behind the popularity of database systems.
However, SQL can be executed only on structured datasets, leaving out of immediate reach …

Computational fact checking,(given a textual claim and a table, verify if the claim holds wrt
the given data) and data-to-text generation (given a subset of cells, produce a sentence …

Several applications, such as text-to-SQL and computational fact checking, exploit the
relationship between relational data and natural language text. However, state of the art …

In the era of Big Data, entity resolution (ER), ie, the process of identifying which records refer
to the same entity in the real world, plays a critical role in data-integration tasks, especially in …