MATE: Multi-Attribute Table Extraction

Knowledge Graph-driven Tabular Data Discovery from Scientific Documents

Automatic Table Union Search with Tabular Representation Learning

Adversarial Attacks on Tables with Entity Swap

GitTables: A Large-Scale Corpus of Relational Tables

JenTab: A Toolkit for Semantic Table Annotations

LakeBench: Fine-Tuning Benchmarks for Data Discovery over Data Lakes

MATE: Multi-Attribute Table Extraction

RECA: Related Tables Enhanced Column Semantic Type Annotation Framework

Starmie: Semantics-aware Dataset Discovery from Data Lakes

Coresets over multiple tables for feature-rich and data-efficient machine learning

CORNET: Learning Table Formatting Rules By Example

DeepJoin Joinable Table Discovery with Pretrained Language Models

DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data

To Join or Not to Join: An Analysis on the Usefulness of Joining Tables in Open Government Data

Integrating Data Lake Tables

Semantic Concept Annotation for Tabular Data

Fair Sequential Group Recommendations in SQUIRREL Movies

Discovering and Integrating Tabular Data

Table Union Search with Preferences

Towards Generative Semantic Table Interpretation

WikiDBs: A Corpus Of Relational Databases From Wikidata

Column Type Annotation using ChatGPT