Yuyang Dong, Chuan Xiao, Takuma Nozawa, Masafumi Enomoto, and Masafumi Oyamada. DeepJoin: Joinable Table Discovery with Pre-Trained Language Models. Proc. VLDB Endow. 16, 10 (June 2023), 2458–2470. https://doi.org/10.14778/3603581.3603587
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30- Disconnect Mode Lab Part 1
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