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Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks
Summary: Table-GPT introduces table fine-tuning for GPT-3.5/ChatGPT: continue-training on synthetic tasks distilled from real relational tables to improve 2D table understanding. Yields consistent gains on data transformation/cleaning/imputation/table-QA, including unseen holdout tasks, while preserving instruction-following generalization.
(summarized by gpt-5.4-mini on May 24 2026)
- Paper ID
- 6940
- Venue
- SIGMOD
- Year
- 2024
- Pagerank
- 8.4909917e-05
- Overall Rank
- 2,585 | 82.04%
- DOI
-
10.1145/3654979
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 19 of 19 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 5,001 |
GenRewrite: Query Rewriting via Large Language Models |
2026 |
SIGMOD |
5.7634197e-05 |
| 7,045 |
Magneto: Combining Small and Large Language Models for Schema Matching |
2025 |
VLDB |
4.8474104e-05 |
| 7,137 |
Automated Validating and Fixing of Text-to-SQL Translation with Execution Consistency |
2025 |
SIGMOD |
4.8165495e-05 |
| 7,369 |
ELEET: Efficient Learned Query Execution over Text and Tables |
2024 |
VLDB |
4.7452331e-05 |
| 8,479 |
Can Large Language Models Be Query Optimizer for Relational Databases? |
2026 |
SIGMOD |
4.4967983e-05 |
| 8,732 |
Unveiling Challenges for LLMs in Enterprise Data Engineering |
2026 |
VLDB |
4.4520434e-05 |
| 9,381 |
Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations |
2024 |
SIGMOD |
4.343902e-05 |
| 9,405 |
TabulaX: Leveraging Large Language Models for Multi-Class Table Transformations |
2025 |
VLDB |
4.3399748e-05 |
| 9,481 |
Data Imputation with Limited Data Redundancy Using Data Lakes |
2025 |
VLDB |
4.3300131e-05 |
| 9,993 |
BridgeScope: A Universal Toolkit for Bridging Large Language Models and Databases |
2026 |
CIDR |
4.1905499e-05 |
| 10,109 |
Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,115 |
ST-Raptor: LLM-Powered Semi-Structured Table Question Answering |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,521 |
Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,597 |
Birdie: Natural Language-Driven Table Discovery Using Differentiable Search Index |
2025 |
VLDB |
4.1905499e-05 |
| 10,606 |
Auto-Prep: Holistic Prediction of Data Preparation Steps for Self-Service Business Intelligence |
2025 |
VLDB |
4.1905499e-05 |
| 10,683 |
On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing |
2025 |
VLDB |
4.1905499e-05 |
| 10,758 |
QUEST: Query Optimization in Unstructured Document Analysis |
2025 |
VLDB |
4.1905499e-05 |
| 10,759 |
Cents: A Flexible and Cost-Effective Framework for LLM-Based Table Understanding |
2025 |
VLDB |
4.1905499e-05 |
| 10,828 |
TableCopilot: A Table Assistant Empowered by Natural Language Conditional Table Discovery |
2025 |
VLDB |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 192 |
HoloClean: Holistic Data Repairs with Probabilistic Inference |
2017 |
VLDB |
0.00035692958 |
| 219 |
Deep Entity Matching with Pre-Trained Language Models |
2021 |
VLDB |
0.00033354456 |
| 293 |
Deep Learning for Entity Matching: A Design Space Exploration |
2018 |
SIGMOD |
0.00028661817 |
| 304 |
Generic Schema Matching with Cupid |
2001 |
VLDB |
0.00028282278 |
| 420 |
InfoGather: Entity Augmentation and Attribute Discovery By Holistic Matching with Web Tables |
2012 |
SIGMOD |
0.00023700634 |
| 514 |
TURL: Table Understanding through Representation Learning |
2021 |
VLDB |
0.00021280726 |
| 516 |
Can Foundation Models Wrangle Your Data? |
2023 |
VLDB |
0.00021194444 |
| 656 |
ERACER: A Database Approach for Statistical Inference and Data Cleaning |
2010 |
SIGMOD |
0.00018590675 |
| 1,316 |
Harvesting Relational Tables from Lists on the Web |
2009 |
VLDB |
0.00012616422 |
| 1,629 |
Data Cleaning: Overview and Emerging Challenges |
2016 |
SIGMOD |
0.00011073148 |
| 1,895 |
Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning |
2020 |
VLDB |
0.00010174634 |
| 2,161 |
Uni-Detect: A Unified Approach to Automated Error Detection in Tables |
2019 |
SIGMOD |
9.4029915e-05 |
| 2,507 |
Auto-Detect: Data-Driven Error Detection in Tables |
2018 |
SIGMOD |
8.6254741e-05 |
| 2,513 |
Annotating Columns with Pre-trained Language Models |
2022 |
SIGMOD |
8.6155767e-05 |
| 2,895 |
Sato: Contextual Semantic Type Detection in Tables |
2020 |
VLDB |
7.9539265e-05 |
| 3,003 |
Chorus: Foundation Models for Unified Data Discovery and Exploration |
2024 |
VLDB |
7.7358219e-05 |
| 3,483 |
Transform-Data-by-Example (TDE): An Extensible Search Engine for Data Transformations |
2018 |
VLDB |
7.0493668e-05 |
| 3,738 |
Auto-Join: Joining Tables by Leveraging Transformations |
2017 |
VLDB |
6.8006812e-05 |
| 3,745 |
TEGRA: Table Extraction by Global Record Alignment |
2015 |
SIGMOD |
6.7907837e-05 |
| 3,982 |
How Large Language Models Will Disrupt Data Management |
2023 |
VLDB |
6.5595332e-05 |
| 4,211 |
Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration |
2023 |
SIGMOD |
6.3495931e-05 |
| 5,279 |
Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using Examples |
2023 |
VLDB |
5.5851818e-05 |
| 5,388 |
Auto-FuzzyJoin: Auto-Program Fuzzy Similarity Joins Without Labeled Examples |
2021 |
SIGMOD |
5.5342724e-05 |
| 6,411 |
Synthesizing Type-Detection Logic for Rich Semantic Data Types using Open-source Code |
2018 |
SIGMOD |
5.0675656e-05 |
| 6,798 |
DTT: An Example-Driven Tabular Transformer for Joinability by Leveraging Large Language Models |
2024 |
SIGMOD |
4.9186164e-05 |
| 7,810 |
Pollock: A Data Loading Benchmark |
2023 |
VLDB |
4.6415099e-05 |
| 7,840 |
Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes |
2021 |
SIGMOD |
4.6337164e-05 |
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