Tabular ML

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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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FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching
Oct 6, 2026Emmanouil Panagiotou, Eirini NtoutsiFlow Matching Explainable Artificial Intelligence
Freie Universität Berlin · University of the Bundeswehr Munich
Scalable extraction and visualization of multi-attribute logical and functional dependencies in tabular data
Oct 6, 2026Chaithra Umesh, Arvind Lomrore, Neethu D +3Tabular ML
Institute of Computer Science, University of Rostock, Germany · School of Data Science, Indian Institute of Science Education and Research, Thiruvananthapuram, India · Leibniz-Institute for Food Systems Biology, Technical University of Munich, Freising, Germany +1
Hybrid Methods for Robust Tabular Data Imputation
Sep 30, 2026Jinwei Li, Michelle Bruch, Daniel TenbrinckIncomplete Data Imputation Tabular ML
Department of Data Science Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen, Germany
Large Language Models for Automated Cross-Domain Machine Learning Task Type Identification: A Benchmark Dataset and Evaluation
Sep 28, 2026Petros Tsialis, Steffen Limmer, Tobias Rodemann +1LLM Evaluation Tabular ML
University of Applied Sciences Aalen · Honda Research Institute Europe
Beyond Correctness: Evaluating Semantic Knowledge in Cross-Table Transfer
Sep 28, 2026Seokyong Sheem, Hochang Lee, Suyeong Lee +1Tabular ML Tabular Prediction
Korea University
CRISP: Scalable Importance-Stratified Coresets for Imbalanced Tabular Learning
Sep 22, 2026Hardhik Mohanty, Indrayana Rustandi, Mohamadreza SheibaniClass-Imbalanced Learning Training Data Selection
University of Southern California Los Angeles, California, USA · Coinbase San Francisco, California, USA
Machine Learning-Based Prediction of Childhood Stunting in Bangladesh: Fairness and Temporal Robustness Assessment
Sep 21, 2026Md Ahshanul Haque, Muhammad Ashad KabirHealthcare Algorithmic Fairness
School of Computing, Mathematics and Engineering, Charles Sturt University, NSW, Australia
Agentic Search Spaces for Tabular Machine Learning
Sep 14, 2026Renat Sergazinov, Artem Chistyakov, Sergey Pankevich +1Large Language Model-Guided Optimization Tabular ML
† Yandex ‡ HSE University
TabBench-Bio: A Living Benchmark for Machine Learning on High-Dimensional Biomedical Tables
Sep 7, 2026Jules Kreuer, Sofiane Ouaari, Julia Hellmig +2Tabular Foundation Models Tabular ML
Methods in Medical Informatics, University of Tübingen, Tübingen, Germany
Scaling Laws, Tabular Data and Actuarial Ratemaking Models
Sep 2, 2026Ronald RichmanTabular ML Scaling Laws
insureai and Bayes Business School, Johannesburg, South Africa
Solving In-Table Prediction Problems by Deep Neural Networks with Performance Evaluation Using Synthetic Data
Sep 1, 2026Xiao Zhao, Daniela OelkeLearning with Missing Data Tabular ML
Institute for Machine Learning and Analytics Offenburg University · Department of Electrical Engineering, Medical Engineering and Computer Science Offenburg University
Actionable CBFI: Integrating Structural Decomposition and Causal Counterfactual Recourse for Tabular Machine Learning
Aug 28, 2026Sejong OhFeature Attribution Counterfactual Explanations
Dankook University, Republic of Korea
TabSOM: A tabular-to-image encoding method based on self-organizing maps
Aug 13, 2026David Chushig-Muzo, María Ángeles Rodríguez de Cara, Eva Milara +3Tabular ML Self-Organizing Maps
School of Mathematical and Computational Sciences, Yachay Tech University, Ecuador
Unlocking the Power of Medical Tabular Data via Semantic-Aware Multimodal Pre-training
Aug 11, 2026Yingsheng Liu, Haiming Li, Jingmin Zhu +6Cross-Modal Representation Learning Multimodal Pretraining
Faculty of Information Technology, Monash University, Melbourne, Australia · Monash University, Melbourne, Victoria, Australia · The University of Queensland, Brisbane, Queensland, Australia
Tabular Numeric Stretch Transformation
Aug 10, 2026Zihao Ye, Juyong Kim, Johnna Sundberg +2Tabular ML Automated Feature Engineering
Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213, USA
GRACE: LLM-Grounded Semantic Metric Spaces for Scalable Mixed-Data Clustering
Aug 8, 2026Zihua Yang, Zhencheng Xie, Junyang Chen +4Clustering Unsupervised Clustering
Guangdong University of Technology · Tsinghua University · Peking University +2
NOMADD: Numerical Optimization of Models Adapting to Data Drift
Aug 3, 2026Swapn Shah, Keith BurghardtConcept Drift Tabular ML
University of North Carolina at Charlotte
Logit-Origin Centering for Singleton Test-Time Adaptation
Aug 2, 2026Mayank Sharma, Rohit Kumar Mourya, Pratik MazumderTest-Time Adaptation Tabular ML
Indian Institute of Technology Jodhpur, Jodhpur, India
Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data
Jul 31, 2026Pulock Das, Yina Hou, Md. Kamrozzaman Bhuiyan +1Class-Imbalanced Learning Clustering
Department of Computer Science Tennessee State University Nashville, TN, USA · Enosis Solutions Dhaka, Bangladesh · Department of Computer Science North Carolina A&T State University Greensboro, NC, USA
TreeCCA: Canonical Correlation Analysis via Gradient-Boosted Trees
Jul 29, 2026James ChapmanGradient-Boosted Decision Trees Multi-View Learning
Adaptive Graph-of-Islands Evolution for Automatic Feature Engineering with LLMs
Jul 25, 2026Sha Li, Naren RamakrishnanEvolutionary Optimization Large Language Model-Guided Optimization
Department of Computer Science Virginia Tech Blacksburg, VA 24060 · Department of Computer Science Virginia Tech Alexandria, VA 22305
Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study
Jul 23, 2026Kaihua DingTabular ML Scaling Laws
University of Pennsylvania
Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models
Jul 22, 2026Yurong Liu, Yeye He, Haoyu Dong +4Incomplete Data Imputation Selective Prediction
New York University · Microsoft Research
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 Perceptrons Tabular 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
Inter-Stop Energy Prediction and Causal Driver Quantification for Dual-Source Trolleybuses via a Time-Aware Tabular Deep Learning Architecture
Jul 13, 2026Wentao Zeng, Zijian Huang, Yiming Bie +2Time Series Forecasting Tabular ML
School of Management, Foshan University, Foshan, China a School of Management, Foshan University, Foshan, China · School of Mechanical and Electrical Engineering and Automation, Foshan University, Foshan, China · School of Management, Foshan University, Foshan 528000, China +7
ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm
Jul 13, 2026Pei Guo, Enjie Liu, Yunzhi Tan +6Tabular ML LLM Reasoning
♠Big Data and AI Platform Department, Tencent, China · ♢Institute of Computer Science and Technology, Soochow University, China
TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning
Jul 6, 2026Yury Gorishniy, Akim Kotelnikov, Ivan Rubachev +1Multilayer Perceptrons Ensemble Learning
1Yandex · 2HSE University
When Does Small Data Work? Accuracy and Efficiency Trade-offs Between Tabular Foundation Models and Conventional Methods for Crowd-State Classification at Hajj and Umrah
Jul 4, 2026AlJawharh S. AlOtaibi, Mohamed Eltahir, Jude AlSubaieTabular Foundation Models Few-Shot Learning
Riyadh, Saudi Arabia
Evolutionary Feature Engineering for Structured Data
Jul 2, 2026Ege Onur Taga, Yilin Zhuang, M. Emrullah Ildiz +4Large Language Model-Guided Optimization Time Series Forecasting
University of Michigan · Google Research
Interpretable vs Learned Encoders for High-Cardinality Fraud Detection
Jul 1, 2026Xiao Han, Jingjing Liu, Moxuan Zheng +2Financial Fraud Detection Tabular ML
Goizueta Business School Emory University Atlanta, GA, USA · Electrical Engineering and Computer Sciences University of California, Berkeley Kirkland, WA · Stern School of Business New York University New York, NY, USA +2

Oct 6, 2026, cs.LGJ/K move · Enter open · S save

FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

Emmanouil Panagiotou, Eirini Ntoutsi

Freie Universität Berlin · University of the Bundeswehr Munich

Flow Matching Explainable Artificial Intelligence Counterfactual Explanations Tabular ML

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In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would lead to a more favourable outcome. To be useful in practice, such an explanation should change few features and change them as little as possible, properties known as sparsity and proximity. We observe that existing methods remain limited in this respect, especially for numerical features, whether they are model-agnostic and amortised, or gradient-based with full access to the model. In this paper, we propose FlowCF, a model-agnostic generative method that frames CF generation as sparse transport from the factual to the target class. We solve this transport with flow matching, which we extend to mixed feature types with a novel mixed flow operator, and exploit the resulting geometry to optimise for sparsity through a gating network that minimises the number of features the transport changes. Extensive experiments on six benchmark datasets demonstrate that FlowCF produces the best numerical sparsity and proximity, changing 29% of the numerical features where the best baseline changes 89%, at 70% smaller displacement, while remaining comparable on the other desiderata.

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