Tabular Classification

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Overview

Tabular classification assigns labels to structured records, supporting tasks such as fraud detection, diagnosis, and credit decisions. Common approaches include decision trees and gradient-boosted ensembles, neural networks, and newer tabular foundation models that use synthetic pretraining or in-context learning; language models and interpretable models are also being adapted to structured features. Benchmarks such as OpenML, TabArena, and TALENT compare methods across datasets, while research also studies imbalance, missingness, calibration, privacy, and inference cost. No method dominates across all data regimes, and a central challenge is balancing predictive performance with compute, reliability, and interpretability.

Latest papers

CardsList

24 papers4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. Multi-Objective Evolutionary Semi-Supervised Learning for Resource-Aware Smart City Classification

    Oct 20, 2026Francisco José Sedeño, Jamal ToutouhSemi-Supervised LearningTabular Classification

    ITIS Software, University of Malaga, Malaga, Spain

  2. FTFM: Factorized Tabular Foundation Models

    Oct 18, 2026Josif GrabockaTabular Foundation ModelsTabular ICL

    University of Technology Nuremberg

  3. From Prompts to Trees: Effective LLM-Guided Tree Generation for Few-Shot Tabular Classification

    Oct 7, 2026Yue Qiu, Zekang Du, Yiqun Diao +2Tabular ClassificationDecision Tree Learning

    School of Computer Science and Technology, Huazhong University of Science and Technology · School of Computing, National University of Singapore

  4. Efficient Provably Private Classification with a Tabular Foundation Model

    Oct 7, 2026Talal Alrawajfeh, Cristiana Diaconu, Ossi Räisä +5Privacy-Preserving MLTabular Foundation Models

    Department of Computer Science, University of Helsinki, Helsinki, Finland · Department of Engineering, University of Cambridge, Cambridge, United Kingdom · CISPA Helmholtz Center for Information Security, Saarbrücken, Germany +1

  5. Distilling Foundation Models for Agentic What-If Reasoning:Cost, Latency, and Governance in a Hybrid LLM+SLM Architecture

    Sep 14, 2026Sourish Dey, Aditya KumarModel CompressionTabular Foundation Models

    Machine Learning SumUp, Berlin

  6. TEFM: Token-Efficient Faithful Modeling for Structured Data

    Sep 9, 2026Zhichao Hou, Lingdao Sha, Xueyu Mao +3LLM InterpretabilityTabular Classification

    North Carolina State University · Amazon Web Services

  7. EXAONE Tabular 1.0 : Technical Report

    Aug 26, 2026Moonjung Eo, Min-Kook Suh, Hye-Seung Cho +4Tabular Foundation ModelsTabular ICL

    LG AI Research

  8. Localized TabICLv2: Scaling Tabular In-Context Learning through k-NN

    Aug 17, 2026Beimnet Bekele GutaTabular ICLTabular Classification

    University of Cambridge, Cambridge, United Kingdom.

  9. Why Large Language Models Fail at Tabular Prediction

    Aug 3, 2026Marta Garnelo, Wojciech M. CzarneckiLLM EvaluationTabular Classification

    Fundamental Technologies

  10. Understanding Context Sampling in TabPFN on Small Tabular Datasets

    Jul 29, 2026Mohammed AbdullahTabular Foundation ModelsTabular Classification

    Department of AI & Data Science Anna University

  11. Is the Statistical Advantage Worth the Cost? An Empirical Comparison of KANs and MLPs for Structured Data Classification

    Jul 15, 2026Matthew Steven P. Toledo, Justine Raphael H. Jacinto, Vivekjeet Singh Chambal +3Multilayer PerceptronsTabular Classification

    Institute of Computer Science, University of the Philippines Los Baños, Philippines · Machine Learning and Artificial Intelligence Applications Lab, University of the Philippines Los Baños, Philippines

  12. Pattern-Aware Graph Neural Networks for Handling Missing Data

    Jul 9, 2026Minett Tran, Taehee JeongGraph Neural NetworksLearning with Missing Data

    San Jose State University

  13. Complexity-Budgeted, Interaction-Aware Interpretable Model for Tabular Data

    Jul 8, 2026Srikumar KrishnamoorthyFeature Interaction ModelingInterpretable ML

    Information Systems Area, Indian Institute of Management Ahmedabad, India

  14. Choosing a parallel heterogeneous ensemble method for tabular classification

    Jul 6, 2026Vassili Maillet, Gustavo, Angulo +1Ensemble LearningTabular Classification

    Jesus · Mines Paris, PSL University, France

  15. Hyperbolic Manifold Constrained Tabular Neural Network

    Jun 23, 2026Tian Li, Huizhi Liang, Lucy Robinson +1Tabular ClassificationTabular Representation Learning

    Newcastle University Newcastle upon Tyne, UK

  16. Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data

    May 26, 2026Tomás Pereira, João Vitorino, Eva Maia +1Feature AttributionExplainable Artificial Intelligence

    GECAD, ISEP, Polytechnic of Porto, Porto, Portugal

  17. Do You Even Need More Data? Rethinking LLM Deployment for Label-Scarce Tabular Classification with TabLens

    May 23, 2026Daria Grushina, Kseniia Kuvshinova, Alina Kostromina +3Zero-Shot LearningLLM Evaluation

    Sb AI Lab, HSE University, NES, Russia · MBZUAI, United Arab Emirates · Sb AI Lab, HSE University, Russia +1

  18. Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification

    May 20, 2026Samuel McDowell, Nathan Stromberg, Lalitha SankarClass-Imbalanced LearningTabular Classification

    School of Electrical, Computer and Energy Engineering · Arizona State University, Tempe, AZ

  19. Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap

    May 18, 2026Aditya Tanna, Yash Desai, Pratinav Seth +3Tabular Foundation ModelsEnsemble Learning

    Lexsi Labs

  20. TabH2O: A Unified Foundation Model for Tabular Prediction

    May 18, 2026Pascal Pfeiffer, Dmitry Gordeev, Mathias Müller +6Tabular Foundation ModelsTabular Classification

  21. TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes

    May 14, 2026Ruizhe Liu, Jiaqi LuoClass-Imbalanced LearningTabular Classification

    School of Mathematical Sciences, Soochow University, No.1 Shizi Street, Suzhou, 215006, Jiangsu Province, China

  22. MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification

    May 12, 2026Bo Zheng, Yudong Chen, Zihua Xiong +4Tabular Foundation ModelsSelf-Supervised Pre-Training

    Zhejiang University · MyBank, Ant Group

  23. BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification

    May 7, 2026Yi-Siang Wang, Kuan-Yu Chen, Yu-Chen Den +1Ensemble LearningLLM Fine-Tuning

    SinoPac Holdings

  24. Quantum-Inspired Geometric Classification with Correlation Group Structures and VQC Decision Modeling

    Apr 2, 2026Nishikanta Mohanty, Arya Ansuman Priyadarshi, Bikash K. Behera +1Tabular ClassificationHybrid Quantum-Classical ML

    Centre for Quantum Software and Information, University of Technology Sydney, 15 Broadway, Ultimo, Sydney, 2007, NSW, Australia. · Bikash’s Quantum (OPC) Pvt. Ltd., Balindi, Mohanpur, 741246, WB, India. · Universit`a degli Studi di Cagliari, Via Is Mirrions, Cagliari, 09123, Italy.