Towards natural language interfaces for data visualization: A survey
Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary
input modality to direct manipulation for visual analytics can provide an engaging user …
input modality to direct manipulation for visual analytics can provide an engaging user …
Machine knowledge: Creation and curation of comprehensive knowledge bases
Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
Turl: Table understanding through representation learning
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 …
tables, there has been tremendous progress on a variety of tasks in the area of table …
Tuta: Tree-based transformers for generally structured table pre-training
We propose TUTA, a unified pre-training architecture for understanding generally structured
tables. Noticing that understanding a table requires spatial, hierarchical, and semantic …
tables. Noticing that understanding a table requires spatial, hierarchical, and semantic …
Annotating columns with pre-trained language models
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 …
columns, is an active research topic in data management as we find many tables are …
From tabular data to knowledge graphs: A survey of semantic table interpretation tasks and methods
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 …
observe that this data format is widely used on the Web and within enterprise data …
Dataset discovery and exploration: A survey
Data scientists are tasked with obtaining insights from data. However, suitable data is often
not immediately at hand, and there may be many potentially relevant datasets in a data lake …
not immediately at hand, and there may be many potentially relevant datasets in a data lake …
Semtab 2019: Resources to benchmark tabular data to knowledge graph matching systems
Abstract Tabular data to Knowledge Graph matching is the process of assigning semantic
tags from knowledge graphs (eg, Wikidata or DBpedia) to the elements of a table. This task …
tags from knowledge graphs (eg, Wikidata or DBpedia) to the elements of a table. This task …
Table pre-training: A survey on model architectures, pre-training objectives, and downstream tasks
Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs,
and various other document types, a flurry of table pre-training frameworks have been …
and various other document types, a flurry of table pre-training frameworks have been …
Large language models for tabular data: Progresses and future directions
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 …
efficiently and accurately understand, process, reason about, analyze, and generate tabular …