mlsanityData to 14 Oct 2026

TabKANet: Tabular Data Modeling with Kolmogorov-Arnold Network and Transformer

arXiv 2409.08806 ↗First posted 13 Sep 2024cs.LG cs.AIcited by 4

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Abstract (arXiv)

Tabular data is the most common type of data in real-life scenarios. In this study, we propose the TabKANet model for tabular data modeling, which targets the bottlenecks in learning from numerical content. We constructed a Kolmogorov-Arnold Network (KAN) based Numerical Embedding Module and unified numerical and categorical features encoding within a Transformer architecture. TabKANet has demonstrated stable and significantly superior performance compared to Neural Networks (NNs) across multiple public datasets in binary classification, multi-class classification, and regression tasks. Its performance is comparable to or surpasses that of Gradient Boosted Decision Tree models (GBDTs). Our code is publicly available on GitHub: https://github.com/AI-thpremed/TabKANet.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 15 of its 29 references that are in the map. First posted on arXiv 13 Sep 2024.

Builds on

15 of 29 references.

References · 15

  1. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  2. 2021Revisiting Deep Learning Models for Tabular Datacited by 740
  3. 2022TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Secondcited by 674
  4. 2024KAN: Kolmogorov-Arnold Networkscited by 649
  5. 2019TabNet: Attentive Interpretable Tabular Learningcited by 648
  6. 2022TabLLM: Few-shot Classification of Tabular Data with Large Language Modelscited by 277
  7. 2023When Do Neural Nets Outperform Boosted Trees on Tabular Data?cited by 223
  8. 2024U-KAN Makes Strong Backbone for Medical Image Segmentation and Generationcited by 179
  9. 2021BERT: A Review of Applications in Natural Language Processing and Understandingcited by 109
  10. 2020Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Datacited by 52
  11. 2024A Temporal Kolmogorov-Arnold Transformer for Time Series Forecastingcited by 52
  12. 2020Sequential Deep Learning for Credit Risk Monitoring with Tabular Financial Datacited by 39
3 more
  1. 2023Trompt: Towards a Better Deep Neural Network for Tabular Datacited by 36
  2. 2024A Benchmarking Study of Kolmogorov-Arnold Networks on Tabular Datacited by 25
  3. 2024HyperKAN: Kolmogorov-Arnold Networks make Hyperspectral Image Classificators Smartercited by 5

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Cited by year

Citing papers per year: 2025: 4.

4 papers.

  1. 2025TabKAN: Advancing Tabular Data Analysis using Kolmogorov-Arnold Networkcited by 3
  2. 2025TabNSA: Native Sparse Attention for Efficient Tabular Data Learningcited by 2
  3. 2025AI-driven Prediction of Insulin Resistance in Normal Populations: Comparing Models and Criteriacited by 0
  4. 2025Basis Transformers for Multi-Task Tabular Regressioncited by 0