mlsanityData to 14 Oct 2026

Graph Neural Network Approach to Semantic Type Detection in Tables

arXiv 2405.00123 ↗First posted 30 Apr 2024cs.LG cs.CLcited by 3

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Abstract (arXiv)

This study addresses the challenge of detecting semantic column types in relational tables, a key task in many real-world applications. While language models like BERT have improved prediction accuracy, their token input constraints limit the simultaneous processing of intra-table and inter-table information. We propose a novel approach using Graph Neural Networks (GNNs) to model intra-table dependencies, allowing language models to focus on inter-table information. Our proposed method not only outperforms existing state-of-the-art algorithms but also offers novel insights into the utility and functionality of various GNN types for semantic type detection. The code is available at https://github.com/hoseinzadeehsan/GAIT

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 17 of its 27 references that are in the map. First posted on arXiv 30 Apr 2024.

Builds on

17 of 27 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  3. 2017Graph Attention Networkscited by 8,923
  4. 2015Gated Graph Sequence Neural Networkscited by 796
  5. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 398
  6. 2017Scene Graph Generation from Objects, Phrases and Region Captionscited by 154
  7. 2021TABBIE: Pretrained Representations of Tabular Datacited by 111
  8. 2020TUTA: Tree-based Transformers for Generally Structured Table Pre-trainingcited by 100
  9. 2019Sherlock: A Deep Learning Approach to Semantic Data Type Detectioncited by 74
  10. 2023Table-GPT: Table-tuned GPT for Diverse Table Taskscited by 69
  11. 2018Iterative Visual Reasoning Beyond Convolutionscited by 38
  12. 2019VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repositorycited by 28
5 more
  1. 2021TCN: Table Convolutional Network for Web Table Interpretationcited by 24
  2. 2023Jellyfish: A Large Language Model for Data Preprocessingcited by 20
  3. 2023Column Type Annotation using ChatGPTcited by 19
  4. 2019Learning Semantic Annotations for Tabular Datacited by 17
  5. 2023ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Modelscited by 15

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026TabEmb: Joint Semantic-Structure Embedding for Table Annotationcited by 1
  2. 2026ReasonEdit: Towards Interpretable Image Editing Evaluation via Reinforcement Learningcited by 1
  3. 2026ZTab: Domain-based Zero-shot Annotation for Table Columnscited by 0