Tabular ML

ML: Machine Learning

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7 papers in the last four weeks, up 17% on the four weeks before. 0.1% of all new papers.

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Latest papers 72

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Exploring Differences Between Tabular Enterprise Data and Public Benchmarks
Jun 29, 2026Myung Jun Kim, Maximilian Schambach, Frank Essenberger +2Benchmark Design Tabular ML
SAP SE, Germany.
Beyond IID: How General Are Tabular Foundation Models, Really?
Jun 29, 2026Lennart Purucker, Andrej Tschalzev, Nick Erickson +7Tabular Foundation Models OOD Generalization
1Prior Labs · University of Mannheim · 4INRIA Saclay +5
EMA-FS: Accelerating GBDT Training via Gain-Informed Feature Screening
Jun 24, 2026Yan SongGradient-Boosted Decision Trees Tabular ML
PayPal, Inc.
Interpretable Concept-Guided Polynomial Tabular Kolmogorov-Arnold Network for EEG-Based Mild Cognitive Impairment Detection
Jun 24, 2026Yosef Bernardus Wirian, Qiang ChengElectroencephalography Interpretable ML
Computer Science Department, University of Kentucky, 351 Ralph G. Anderson Building, Lexington, 40506, KY, USA · Institute for Biomedical Informatics, University of Kentucky, 760 Press Ave, 40508, Lexington, KY, USA
When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning
Jun 18, 2026Daehwan Kim, Haejun Chung, Ikbeom JangSelf-Supervised Learning Tabular ML
Hanyang University, Seoul, South Korea · Hankuk University of Foreign Studies, Yongin, South Korea
Parameter-Efficient Adapter Tuning for Tabular-Image Multimodal Learning
Jun 10, 2026Jiaqi LuoFine-Tuning Adapter Tuning
School of Mathematical Sciences, Soochow University, No.1 Shizi Street, Suzhou, 215006, Jiangsu Province, China
LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version)
Jun 8, 2026Ankai Hao, Ke Chen, Huan Li +1LLM Evaluation Tabular ML
Zhejiang University
Towards Pretraining Text Encoders for TabPFN
Jun 3, 2026Mustafa Tajjar, Alexander Pfefferle, Lennart Purucker +1Tabular Foundation Models Fine-Tuning
Department of Computer Science, University of Freiburg, Freiburg, Germany · ELLIS Institute Tübingen, Tübingen, Germany · Prior Labs, Freiburg, Germany.
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Jun 1, 2026Andrej Tschalzev, Nick Erickson, Yuyang Wang +4Tabular ML Automated Feature Engineering
University of Mannheim · Prior Labs · AWS +3
Segment-driven Structural Induction and Semantic Alignment for Heterogeneous Tabular Representation
Jun 1, 2026Woojun Jung, Susik YoonTabular Foundation Models Self-Supervised Pre-Training
Department of Computer Science & Engineering, Korea University, Seoul, South Korea.
Profiling Privacy Preservation Against Gradient Inversion Attacks in Tabular Federated Learning
May 31, 2026Ivo Osterberg Nilsson, Maximilian Birr Engvall, Viktor Valadi +1Gradient Inversion Attacks Adversarial Attacks
Department of Computing, Jönköping University, Jönköping, Sweden · Scaleout Systems, Uppsala, Sweden · Department of Information Systems, University of Haifa, Haifa, Israel
TabChange: Precise Attribute Changes in Tabular Data
May 30, 2026Arjun Dahal, Yu Lei, Raghu N. Kacker +1Adversarial Representation Learning Counterfactual Explanations
The University of Texas at Arlington · Arlington, Texas, USA · Information Technology Laboratory +2
Statistical Embeddings for Similarity, Retrieval, and Interpretable Alignment of Numeric Tabular Datasets
May 28, 2026M. Ross Kunz, John Merickel, Keith WilsonTabular ML Information Retrieval
1*Idaho National Laboratory.
Open World Autoencoding Drift Detection with Novel Class Recognition in Tabular Non-stationary Data Streams
May 28, 2026Joanna KomorniczakConcept Drift Autoencoders
Department of Systems and Computer Networks, Wrocław University of Science and Technology
Explaining Tabular Foundation Model Differences Through Meta-Features
May 27, 2026Markus Herre, Andrej Tschalzev, Sascha Marton +1Tabular Foundation Models Tabular ML
Clausthal University of Technology, Clausthal-Zellerfeld, Germany · University of Mannheim, Mannheim, Germany
Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
May 26, 2026Tomás Pereira, João Vitorino, Eva Maia +1Feature Attribution Explainable Artificial Intelligence
GECAD, ISEP, Polytechnic of Porto, Porto, Portugal
Trajectory-Based Difficulty Scoring for Reliable Learning on Tabular Data
May 23, 2026Tomer Lavi, Bracha Shapira, Nadav RappoportGradient-Boosted Decision Trees Tabular ML
Faculty of Computer and Information Science, Ben-Gurion University of the Negev, Israel.
Machine-Learning-Enhanced Non-Invasive Testing for MASLD Fibrosis: Shallow-Deep Neural Networks Versus FIB-4, Tabular Foundation Models, and Large Language Models
May 19, 2026Athanasios Angelakis, Gabriele De Vito, Eleni-Myrto Trifylli +1Shallow Neural Networks Tabular ML
BioML Lab, RI CODE, UniBw, Munich, Germany · Department of Epidemiology and Data Science, Amsterdam UMC, Amsterdam, Netherlands · Alpha Indicium, Rijswijk, Netherlands +2
Multi-Dimensional Model Integrity and Responsibility Assessment Index and Scoring Framework
May 14, 2026Phuc Truong Loc Nguyen, Thanh Hung Do, Truong Thanh Hung Nguyen +1Tabular ML Responsible AI
† Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany · ‡ University of New Brunswick, Canada
STRABLE: Benchmarking Tabular Machine Learning with Strings
May 12, 2026Gioia Blayer, Myung Jun Kim, Félix Lefebvre +8Tabular ML Tabular Prediction
SODA Team, INRIA Saclay, Palaiseau, France · Prior Labs · University of Freiburg +3
MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification
May 12, 2026Bo Zheng, Yudong Chen, Zihua Xiong +4Tabular Foundation Models Self-Supervised Pre-Training
Zhejiang University · MyBank, Ant Group
ASD-Bench: A Four-Axis Comprehensive Benchmark of AI Models for Autism Spectrum Disorder
May 11, 2026Shubhankit Singh, Hassan Shaikh, Kuldeep Raghuwanshi +1Probability Calibration Autism Spectrum Disorder
Research Commons AI · IIT Bombay · IIT Delhi
When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detection
May 11, 2026Wei Huang, Hezhe Qiao, Kailai Zhang +3Test-Time Adaptation Tabular Anomaly Detection
SeBA: Semi-supervised few-shot learning via Separated-at-Birth Alignment for tabular data
May 8, 2026Kacper Jurek, Wojciech Batko, Marek Śmieja +1Multi-View Learning Few-Shot Learning
Jagiellonian University, Faculty of Mathematics and Computer Science · AGH University of Krakow
Approximation-Free Differentiable Oblique Decision Trees
May 8, 2026Subrat Prasad Panda, Blaise Genest, Arvind EaswaranInterpretable ML Tabular ML
College of Computing and Data Science Nanyang Technological University Singapore
Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection
May 7, 2026Victor Livernoche, Jie Zan, Reihaneh RabbanyTabular Anomaly Detection Unsupervised Anomaly Detection
McGill University, Mila, Montréal, Canada
TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding
May 6, 2026Minjie Qiang, Mingming Zhang, Xiaoyi Bao +5Tabular Foundation Models Tabular ML
Natural Language Processing Lab, Soochow University, Suzhou, China · Ant Group, Hangzhou, China · The Hong Kong Polytechnic University, Hong Kong, China
ITBoost: Information-Theoretic Trust for Robust Boosting
May 6, 2026Ye Su, Longlong Zhao, Diego Garcia-Gil +4Gradient-Boosted Decision Trees Ensemble Learning
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Department of Software Engineering, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada +1
TabSurv: Adapting Modern Tabular Neural Networks to Survival Analysis
May 5, 2026Stanislav Kirpichenko, Andrei Konstantinov, Lev UtkinSurvival Analysis Deep Ensembles
Higher School of Artificial Intelligence Technologies, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data
May 5, 2026Al Zadid Sultan Bin Habib, Gianfranco Doretto, Donald A. AdjerohDynamic Neural Networks Tabular ML
Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA · Scientific Computing and Imaging Institute & Department of Biomedical Informatics, The University of Utah, Salt Lake City, UT 84112, USA

Jun 29, 2026, cs.LGJ/K move · Enter open · S save

Exploring Differences Between Tabular Enterprise Data and Public Benchmarks

Myung Jun Kim, Maximilian Schambach, Frank Essenberger, Andre Sres+1

SAP SE, Germany.

Benchmark Design Tabular ML Benchmark Validity Tabular Prediction

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Tabular data dominate the landscape of data science, increasingly attracting innovative machine learning models and tailored benchmarks. Yet, little is known for enterprise data, where tables constitute the backbone of business operations. To broaden the benchmarking landscape for business applications, this work aims to actualize the characteristics of enterprise data by providing an analysis of data statistics and performance measurements of tabular models such as TabPFN, TabICL and ConTextTab. Through our analysis, we find enterprise data markedly differ from tabular benchmarks and we demonstrate that a tabular model that performs well on typical tabular benchmarks may perform poorly on real world enterprise data -- and vice versa. This lack of generalization underlines the need for additional benchmarks with enterprise-grade characteristics.

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Latest papers 72