Tabular 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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Beyond Correctness: Evaluating Semantic Knowledge in Cross-Table Transfer
Sep 28, 2026Seokyong Sheem, Hochang Lee, Suyeong Lee +1Tabular Learning Ablation
Korea University
NPBoost: Neural Processes with Gradient-Boosted Fixed Effects
Sep 23, 2026Andrea Nava, Ken Rölli, Armin Begic +1Meta-Learning Neural Processing Units
Seminar for Statistics, ETH Zurich, Switzerland · Lucerne University of Applied Sciences and Arts, Switzerland
CRISP: Scalable Importance-Stratified Coresets for Imbalanced Tabular Learning
Sep 22, 2026Hardhik Mohanty, Indrayana Rustandi, Mohamadreza SheibaniImbalanced Classification Geometry-Aware Uncertainty Coresets
University of Southern California Los Angeles, California, USA · Coinbase San Francisco, California, USA
PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models
Sep 20, 2026Qi Qin, Erbo Li, Ting Wei +4Tabular Learning Tabular Foundation Models
Center for Applied Statistics, School of Statistics, Renmin University of China
Agentic Search Spaces for Tabular Machine Learning
Sep 14, 2026Renat Sergazinov, Artem Chistyakov, Sergey Pankevich +1Tabular Learning General Grid Search Framework
† Yandex ‡ HSE University
Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Search
Sep 9, 2026Rui Liu, Tao Zhe, Yanyong Huang +5Tabular Learning Equivariant Learning
University of Kansas Lawrence, United States · Southwest University of Finance and Economics Chengdu, China · University of Wisconsin–Madison Madison, United States +3
TabBench-Bio: A Living Benchmark for Machine Learning on High-Dimensional Biomedical Tables
Sep 7, 2026Jules Kreuer, Sofiane Ouaari, Julia Hellmig +2Tabular Learning Biomedical
Methods in Medical Informatics, University of Tübingen, Tübingen, Germany
Scaling Laws, Tabular Data and Actuarial Ratemaking Models
Sep 2, 2026Ronald RichmanActuarial Ratemaking 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 OelkeTabular Learning Tabular Data
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 Importance Tabular Learning
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 Learning Interpretability
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 +6Multimodal Clinical Data Tabular Learning
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 Learning Unsupervised
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 Cluster
Guangdong University of Technology · Tsinghua University · Peking University +2
SkillTFM: Gated Skill Evolution for Training-Free Adaptation of Tabular Foundation Models
Aug 6, 2026Yi He, Zhengkang Guan, Anpeng Wu +3Tabular Foundation Models Tabular Learning
Zhejiang University, Hangzhou, China · Tsinghua University, Beijing, China
Enhancing Tabular Learners with Context-Aware Semantic Embeddings
Aug 4, 2026Günther Schindler, Maximilian Schambach, Johannes HöhneTabular Learning Text Embeddings
SAP SE
Test-Time Augmentation for Tabular-to-Image Classifiers under Distribution Shifts
Aug 4, 2026Malena Loza, Felipe Grijalva, Eva Milara +3Tabular Learning Distribution Shifts
Colegio de Ciencias e Ingenierías, Universidad San Francisco de Quito (USFQ), Quito, Ecuador · Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain · Faculty of Experimental Sciences, Universidad Francisco de Vitoria, Madrid, Spain
NOMADD: Numerical Optimization of Models Adapting to Data Drift
Aug 3, 2026Swapn Shah, Keith BurghardtTabular Prior-Data Fitted Network Tabular Learning
University of North Carolina at Charlotte
Memory Efficient Tabular Foundation Models
Jul 30, 2026Shuting Luo, Monika Mikhail Kanaan, Cameron Gordon +2Tabular Foundation Models Tabular Learning
Commonwealth Bank of Australia, Australia · Australian Institute for Machine Learning, University of Adelaide, Adelaide, Australia
Understanding Context Sampling in TabPFN on Small Tabular Datasets
Jul 29, 2026Mohammed AbdullahTabular Learning Tabular Prior-Data Fitted Network
Department of AI & Data Science Anna University
Adaptive Graph-of-Islands Evolution for Automatic Feature Engineering with LLMs
Jul 25, 2026Sha Li, Naren RamakrishnanFeature Engineering Tabular Learning
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 Learning Scaling Laws
University of Pennsylvania
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 +3Kolmogorov-Arnold Networks Multilayer Perceptrons
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 +2Electricity Price Forecasting Transport
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
TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data
Jul 11, 2026Jiaqi Luo, Shixin XuTabular Learning Gradient Boosted Decision Tree
School of Mathematical Sciences, Soochow University, No.1 Shizi Street, Suzhou, 215006, Jiangsu Province, China · Digital innovation research center, Duke Kunshan University, No.8 Duke Avenue, Kunshan, 215000, Jiangsu Province, China
Complexity-Budgeted, Interaction-Aware Interpretable Model for Tabular Data
Jul 8, 2026Srikumar KrishnamoorthyFeature Importance Interpretability
Information Systems Area, Indian Institute of Management Ahmedabad, India
TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning
Jul 6, 2026Yury Gorishniy, Akim Kotelnikov, Ivan Rubachev +1Tabular Learning Ensemble
1Yandex · 2HSE University
Choosing a parallel heterogeneous ensemble method for tabular classification
Jul 6, 2026Vassili Maillet, Gustavo, Angulo +1Ensemble Tabular Learning
Jesus · Mines Paris, PSL University, France
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 Tabular Learning
Riyadh, Saudi Arabia
Probing Memorization of Tabular In-Context Learning
Jun 30, 2026Francesco Capano, Jonas BöhlerParametric Memory Tabular Learning
SAP SE, Walldorf, Germany.
FlexTab: A Flexible Encoder-Decoder Architecture for In-Context Learning Across Diverse Tabular Tasks
Jun 29, 2026Marek Polewczyk, Maximilian Schambach, Marco Spinaci +2Tabular Learning Tabular Data
1SAP SE · 2SAP France
Accelerometry-Derived Digital Biomarkers for Cardiometabolic Risk: A Population-Representative Tabular Benchmark with Uncertainty Quantification
Jun 29, 2026Federico FelizziCardiovascular Risk Prediction Diabetes
SIIAM, Rome, Italy · enGene Statistics, Basel, Switzerland.
Hyperbolic Manifold Constrained Tabular Neural Network
Jun 23, 2026Tian Li, Huizhi Liang, Lucy Robinson +1Tabular Learning Neural Network
Newcastle University Newcastle upon Tyne, UK
When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning
Jun 18, 2026Daehwan Kim, Haejun Chung, Ikbeom JangTabular Learning Pose-Based Bin-Picking Pipeline
Hanyang University, Seoul, South Korea · Hankuk University of Foreign Studies, Yongin, South Korea
Bounded Context Management for Tabular Foundation Models on Stream Learning
Jun 17, 2026Jinmo Lee, Doyun Choi, Moongi Choi +1Tabular Foundation Models Tabular Learning
Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea · The Kim Jaechul Graduate School of AI, KAIST, Daejeon, Republic of Korea.
Revisiting Structural Dependency in Autoregressive Multi-Task Table Recognition via Order-Independent Cell-Level Representations
Jun 16, 2026Takaya KawakatsuTabular Learning Multi--Task Learning
Preferred Networks, Inc., 1-6-1 Otemachi, Chiyoda, Tokyo, Japan.
TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning
Jun 10, 2026Ruxue Shi, Yili Wang, Mengnan Du +3Tabular Learning Graph Neural Networks
Jilin University Changchun, China · The Chinese University of Hong Kong, Shenzhen Shenzhen, China
TRL-Bench: Standardizing Cross-Paradigm Representation-Level Evaluation of Tabular Encoders
Jun 8, 2026Wei Pang, Xiangru Jian, Hehan Li +10Tabular Learning Multi-Dimensional Evaluation
The Chinese University of Hong Kong, Shenzhen · University of Waterloo · The University of Hong Kong +2
RACT: Retrieval Augmented Column-Table Learning and Prediction for Multi-Table Schema Matching
Jun 5, 2026Leonard Traeger, Enas Khwaileh, Andreas Behrend +1Schema Tabular Learning
University of Maryland, Baltimore County, USA · Utrecht University Utrecht, The Netherlands · Technical University of Cologne Cologne, Germany
Bias in Filter Feature Selection Evaluation: A Meta-Analysis of Datasets, Baselines, and Experimental Design Choices
Jun 5, 2026Malick Ebiele, Malika Bendechache, Rob BrennanFeature Selection False Discovery Rate
1*Computer Science, University College Dublin, Dublin, Dublin, Ireland. · 3ADAPT Centre, Dublin, Dublin, Ireland. · 2Computer Science, University of Galway, Galway, Galway, Ireland.
RowNet: A Memory Transformer for Tabular Regression
Jun 3, 2026Askat Rakhymbekov, Gulshat MuhametjanovaTabular Learning Retrieval Layer
Department of Applied Mathematics and Informatics Kyrgyz-Turkish Manas University Bishkek, Kyrgyzstan · Department of Applied Mathematics and Informatics2026 Kyrgyz-Turkish Manas University Bishkek, KyrgyzstanJun
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Jun 1, 2026Andrej Tschalzev, Nick Erickson, Yuyang Wang +4Tabular Learning Feature Engineering
University of Mannheim · Prior Labs · AWS +3
Algorithmic Recourse of In-Context Learning for Tabular Data
May 29, 2026Wenshuo Dong, Jiaming Zhang, Shaopeng Fu +3Tabular Learning In-Context Learning
King Abdullah University of Science and Technology, Saudi Arabia · Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates · University of Copenhagen, Denmark +2
The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction
May 28, 2026Shu Wan, Abhinav Gorantla, Huan Liu +1Tabular Learning Clinical Prediction
Arizona State University Tempe, United States
Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
May 26, 2026Tomás Pereira, João Vitorino, Eva Maia +1Explainability Explainable AI Methods
GECAD, ISEP, Polytechnic of Porto, Porto, Portugal
LUCoS: Latent Unsupervised Context Selection for Tabular Foundation Models
May 26, 2026Oroel Ipas, Guillermo Gomez-Trenado, Rocío Romero-Zaliz +1Tabular Foundation Models Tabular Learning
1Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) · Department of Computer Science and Artificial Intelligence (DECSAI) · 3Research Center in Information and Communication Technologies (CITIC) +1
Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
May 26, 2026Yusuf Brima, Marcellin Atemkeng, Lansana Hassim Kallon +4Tabular Foundation Models Tabular Learning
Computer Vision, Institute of Cognitive Science, Osnabrück University, Germany · Department of Mathematics, Rhodes University, South Africa · National Institute for Theoretical and computational Sciences (NITheCS), Stellenbosch, 7600, South Africa +6
LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots
May 23, 2026Daria Grushina, Kseniia Kuvshinova, Alina Kostromina +3Tabular Learning
Sb AI Lab, HSE University, NES · NES · Russia +4
Hinge Regression Trees and HRT-Boost: Newton-Optimized Oblique Learning for Compact Tabular Models
May 22, 2026Hongyi Li, Jun Xu, Hong YanDecision Trees Tabular Learning
School of Intelligence Science and Engineering, Harbin Institute of Technology, Shenzhen, 518055, China and with the Shenzhen Key Lab for Advanced Motion Control and Modern Automation Equipments, Shenzhen, 518055, China · Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong
Learning Causal Orderings for In-Context Tabular Prediction
May 21, 2026Sascha Xu, Sarah Mameche, Jilles VreekenCausal Discovery Methods Tabular Learning
CISPA Helmholtz Center
TabH2O: A Unified Foundation Model for Tabular Prediction
May 18, 2026Pascal Pfeiffer, Dmitry Gordeev, Mathias Müller +6Tabular Learning Tabular Data
TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data
May 16, 2026Cormac Cureton, Narges ArmanfardTabular Learning Tabpfn
McGill University · Mila - Quebec AI Institute · Montreal, QC, Canada
TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes
May 14, 2026Ruizhe Liu, Jiaqi LuoTabular Learning Imbalanced Classification
School of Mathematical Sciences, Soochow University, No.1 Shizi Street, Suzhou, 215006, Jiangsu Province, China
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 Learning Scoring
† Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany · ‡ University of New Brunswick, Canada
LoMETab: Beyond Rank-1 Ensembles for Tabular Deep Learning
May 14, 2026Changryeol Choi, Hyewon Park, Yujin Kwon +1Tabular Learning Ensemble
CJ Logistics
XAI and Statistical Analysis for Reliable Intrusion Detection in the UAVIDS-2025 Dataset: From Tree to Hybrid and Tabular DNN Ensembles
May 13, 2026Iakovos-Christos Zarkadis, Christos DouligerisIntrusion Detection Drone Detection
University of Piraeus Athens, Greece · Dept. of Informatics University of Piraeus Piraeus, Greece
STRABLE: Benchmarking Tabular Machine Learning with Strings
May 12, 2026Gioia Blayer, Myung Jun Kim, Félix Lefebvre +8Tabular Learning Mle-Bench Lite
SODA Team, INRIA Saclay, Palaiseau, France · Prior Labs · University of Freiburg +3
Resilient Vision-Tabular Multimodal Learning under Modality Missingness
May 12, 2026Camillo Maria Caruso, Valerio Guarrasi, Paolo SodaMissing Modalities Multimodal Learning
Research Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Università Campus Bio-Medico di Roma, Roma, Italy, Europe · Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Umeå, Sweden, Europe
MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification
May 12, 2026Bo Zheng, Yudong Chen, Zihua Xiong +4Tabular Learning Pretraining
Zhejiang University · MyBank, Ant Group
MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image
May 11, 2026Alan Arazi, Eilam Shapira, Shoham Grunblat +8Tabular Learning Tabular Foundation Models
Technion – Israel Institute of Technology · Prior Labs · NVIDIA +4

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Beyond Correctness: Evaluating Semantic Knowledge in Cross-Table Transfer

Seokyong Sheem, Hochang Lee, Suyeong Lee, Daekyum Kim

Korea University

Tabular Learning Ablation Cross-Task Knowledge Transfer Correctness

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Semantic knowledge is increasingly used to bridge heterogeneous schemas in tabular learning, but how much does that knowledge actually improve prediction? Studies in tabular learning commonly answer this question through semantic ablations that modify or suppress the supplied semantic knowledge. We show that these ablations can lead to misleading conclusions about predictive benefit: poor performance under altered semantics may be taken as evidence that the intended knowledge is beneficial. Across real and controlled experiments, altering semantic content can produce large performance differences even when the model gains little predictive benefit from having that semantic knowledge in the first place. To separate these effects, we distinguish two quantities: content sensitivity and predictive utility. Content sensitivity measures the change in performance when semantic content is altered, whereas predictive utility measures the benefit of the intended semantic knowledge relative to a suitable reference without that knowledge. This distinction motivates an evaluation framework in which the control is chosen according to the question being asked: altered controls assess sensitivity to semantic content, whereas claims that semantic knowledge improves prediction require a suitable reference. Even then, predictive utility is not fixed; it varies across suitable references and decreases when the reference can more easily recover the tested knowledge from other inputs or labeled examples. In a bounded audit of 25 semantic-ablation comparisons across nine studies, only one of 18 explicit predictive-utility claims is paired with a control that clearly isolates the tested semantic contribution. Together, these findings motivate a simple evaluation principle: semantic-ablation controls should be chosen and interpreted according to the question they are intended to answer.

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