Tabular Data

Ask about this field

Recent momentum

emerging

0 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this field, kept on the site without email delivery.

Period ending 2026-09-21

12 new papers

A weekly snapshot of new work published in Tabular Data.

Period ending 2026-09-14

7 new papers

A weekly snapshot of new work published in Tabular Data.

Period ending 2026-09-07

10 new papers

A weekly snapshot of new work published in Tabular Data.

Inside this field

Focused directions

322 papers

Latest in Tabular Data

Browse all topics →
CardsList

  1. Enhancing Tabular Learners with Context-Aware Semantic Embeddings

    Aug 4, 2026Günther Schindler, Maximilian Schambach, Johannes HöhneTabular LearningGlobal Embeddings

  2. NOMADD: Numerical Optimization of Models Adapting to Data Drift

    Aug 3, 2026Swapn Shah, Keith BurghardtTabular Prior-Data Fitted NetworkTabular Learning

  3. Why Large Language Models Fail at Tabular Prediction

    Aug 3, 2026Marta Garnelo, Wojciech M. CzarneckiLarge Language Model PerformanceTabular Data

  4. LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation

    Aug 3, 2026Zijian Shen, Taijie Chen, Bin Zhou +2Synthetic Tabular DataTabular Data

  5. CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives

    Aug 3, 2026Zifan Zhang, Zhichao Hou, Tingxiang Ji +1Multivariate Telemetry DataLong-Horizon Forecasting

  6. TabDPT-Turbo: Efficient In-Context Learning for Tabular Prediction

    Aug 2, 2026Rasa Hosseinzadeh, Alex Labach, Zexin Xue +3Tabular Foundation ModelsIn-Context Learning

  7. Logit-Origin Centering for Singleton Test-Time Adaptation

    Aug 2, 2026Mayank Sharma, Rohit Kumar Mourya, Pratik MazumderTabular LearningContinual Test-Time Adaptation

  8. From field-scale to large-scale spectral libraries: Tabular foundation models in soil spectroscopy

    Aug 1, 2026Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers +1Soil Moisture EstimationSpectra

  9. Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data

    Jul 31, 2026Pulock Das, Yina Hou, Md. Kamrozzaman Bhuiyan +1Extreme Class ImbalanceClass Imbalance

  10. Curriculum Matters: Data-Efficient Relational PFN Pretraining with Synthetic Data

    Jul 31, 2026Mohammad Sadeq Abolhasani, Viswanath GanapathyTabular Prior-Data Fitted NetworkRelational Deep Learning

  11. Revisiting Predictive Process Monitoring in the Age of Foundation Models: A Comparative Study of Sequence, Tabular, and LLM Approaches

    Jul 30, 2026Lennart Fertig, Lukas Kirchdorfer, Tobias SesterhennSequence ModelingNext Activity Prediction

  12. Memory Efficient Tabular Foundation Models

    Jul 30, 2026Shuting Luo, Monika Mikhail Kanaan, Cameron Gordon +2Tabular Foundation ModelsTabular Prior-Data Fitted Network

  13. Understanding Context Sampling in TabPFN on Small Tabular Datasets

    Jul 29, 2026Mohammed AbdullahTabular LearningTabular Prior-Data Fitted Network

  14. Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

    Jul 28, 2026Malena Loza, David Chushig-Muzo, Eva Milara +3Tabular Foundation ModelsTabpfn

  15. Detecting Knowledge Inconsistencies Across Text, Tables, and Knowledge Graphs

    Jul 28, 2026Fanfu Wei, Thibault Ehrhart, Raphaël TroncyKnowledge GraphsKnowledge Gaps

  16. Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners

    Jul 28, 2026Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1In-Context LearningCausal Representation Learning

  17. TabRank: Chain-of-Thought Distillation for Table Re-Rankers

    Jul 28, 2026Adarsh Singh, Kushal Raj Bhandari, Jianxi Gao +2RerankingTabular Data

  18. Impute On-Demand: Adaptive Correlated Time Series Imputation for Changing Environments

    Jul 26, 2026Zhichen Lai, Huan Li, Dalin Zhang +3Multivariate Time Series ImputationInternet Of Thing

  19. Logit-Coordinate Generative Models for Mixed Continuous-Categorical Tabular Data

    Jul 25, 2026Yuefei Shen, Xiaotong ShenMixture ModelsLogit Lens

  20. Adaptive Graph-of-Islands Evolution for Automatic Feature Engineering with LLMs

    Jul 25, 2026Sha Li, Naren RamakrishnanFeature EngineeringTabular Learning

  21. Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study

    Jul 23, 2026Kaihua DingPower-Law DistributionMachine Learning

  22. CURED: Creating, Understanding, and Repairing Errors Demonstrator

    Jul 22, 2026Nicholas Chandler, Sebastian Jäger, Philipp Jung +1Tabular DataErrors

  23. Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models

    Jul 22, 2026Yurong Liu, Yeye He, Haoyu Dong +4Tabular DataMissing Data

  24. In-Context Time Series Classification with Random Convolutional Features

    Jul 21, 2026Joscha Cüppers, Jilles VreekenTime-Series ClassificationTemporal Convolutional Networks

  25. Topological Signatures of Context-Level Reliability in TabPFN

    Jul 20, 2026James Hu, Mahdi GhelichiPersistent HomologyTabular Prior-Data Fitted Network

  26. Semantically Similar, Logically Distinct: Diagnosing the Semantic-Answerability Gap in Table RAG

    Jul 20, 2026Jiaming Tian, Liyao Li, Wentao Ye +5Tabular DataSemantic Gap

  27. Deep and Probabilistic Models for Gene Regulatory Network Inference

    Jul 17, 2026Claudia Skok GibbsGene-Regulatory NetworksGenomics

  28. Revisiting data-driven dynamic security assessment with a tabular foundation model

    Jul 17, 2026Olayiwola Arowolo, Maosheng Yang, Jochen CremerPower SystemsTabular Foundation Models

  29. Gold-Guided Programmatic Distillation for Financial Reasoning over Hybrid Tables and Text

    Jul 16, 2026Yun Dong, Erica Zhao, Elana ChenRationalesOntology-Amplified Distillation

  30. Evaluation Ability Does Not Imply Optimization Utility: LLM-as-a-Judge Signals in Closed-Loop Table Recognition

    Jul 15, 2026Donghwan KimLlm-As-A-JudgeFeedback Learning

  31. Tabular Foundation Models for Discrete Choice Estimation

    Jul 14, 2026Liu Liu, Dan ZhangDiscrete Choice ModelsTabular Foundation Models

  32. Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval

    Jul 14, 2026Qingcheng Zeng, Puxuan Yu, Aman Mehta +2Text-To-SqlSchema

  33. DAG-FM: A Foundation Model for Causal Discovery under Heterogeneous Causal Mechanisms

    Jul 13, 2026Yikang Chen, Zhengkang Guan, Haoyuan Qian +3Causal Foundation ModelsStructural Causal Model

  34. Surprisingly Simple and Effective Multi-Domain Graph Foundation Model through Graph-to-Table Alignment

    Jul 13, 2026Chunyu Hu, Tianyin Liao, Ge Lan +4Graph Foundation ModelTabular Foundation Models

  35. 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 ForecastingTransit Network Design

  36. ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm

    Jul 13, 2026Pei Guo, Enjie Liu, Yunzhi Tan +6Tabular DataTable Reasoning Datasets

  37. TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings

    Jul 13, 2026Jingxiang Zhang, Lujia Zhong, Zijie Zhu +2Multimodal ClassificationMultimodal Embeddings

  38. Observation-Level Watermarking and Detection for Tabular Data

    Jul 12, 2026Dongyu Cui, Xuan BiWatermarkingWatermarks

  39. TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data

    Jul 11, 2026Jiaqi Luo, Shixin XuTabular LearningTabular Data

  40. The Importance of Encoder Choice:A Tabular-Image Study

    Jul 8, 2026Ilia Koloiarov, Diego Coello de Portugal Mecke, Vijaya Krishna Yalavarthi +2Modality-Specific EncodersEncoders

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

    Jul 8, 2026Srikumar KrishnamoorthyFeature ImportanceTabular Learning

  42. TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning

    Jul 6, 2026Yury Gorishniy, Akim Kotelnikov, Ivan Rubachev +1Tabular LearningHyperparameter Optimization

  43. Choosing a parallel heterogeneous ensemble method for tabular classification

    Jul 6, 2026Vassili Maillet, Gustavo, Angulo +1EnsembleTabular Learning

  44. Parameter-Free Encoders Remain Viable for RDB Foundation Models

    Jul 6, 2026Linjie Xu, David WipfEncoding ModelsTabular Foundation Models

  45. Context-Constrained Transfer Learning for Tabular Foundation Models via Data Distillation

    Jul 6, 2026Yijun Lin, Sai LiTabular Foundation ModelsTransfer Learning

  46. 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 ModelsTabular Learning

  47. TabQueryBench: A Query-Centric Benchmark for Synthetic Tabular Data

    Jul 4, 2026Jialin Zhang, Fenghao Dong, Yajie Zhou +2Synthetic Tabular DataTabular Data

  48. Alignment-Guided Largest Table Overlap Size Estimation

    Jul 3, 2026Ge Lee, Shixun Huang, Zhifeng Bao +2Tabular DataFeature Alignment

  49. Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence

    Jul 2, 2026Zhenghua Pan, Ahmed Aziz EzzatElectricity Price ForecastingTime Series Foundation Models

  50. Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines

    Jul 1, 2026Eliott Thomas, Mickael Coustaty, Aurelie Joseph +3Active LearningObject Detection

  51. ConRTF: Edge-Constrained Boundary Distribution Refinement for Realtime TransFormer Table Structure Recognition

    Jul 1, 2026Eliott Thomas, Tri-Cong Pham, Mickael Coustaty +5Rt-DetrTabular Data

  52. Modal CEGAR-tableaux with RECAR and resolution-based SAT-shortcuts

    Jun 30, 2026Rajeev Goré, Cormac KikkertSatisfiabilityTheorem

  53. Probing Memorization of Tabular In-Context Learning

    Jun 30, 2026Francesco Capano, Jonas BöhlerTabular LearningMemorization

  54. Can Tabular In-Context Learners Generalize to Biomolecular Property Prediction?

    Jun 30, 2026Davy Guan, Lu Zhang, Asiri Wijesinghe +7Molecular Property PredictionTabular Foundation Models

  55. Exploring Differences Between Tabular Enterprise Data and Public Benchmarks

    Jun 29, 2026Myung Jun Kim, Maximilian Schambach, Frank Essenberger +2Tabular DataBenchmark Datasets

  56. Beyond IID: How General Are Tabular Foundation Models, Really?

    Jun 29, 2026Lennart Purucker, Andrej Tschalzev, Nick Erickson +7Tabular Foundation ModelsBenchmark Datasets

  57. FlexTab: A Flexible Encoder-Decoder Architecture for In-Context Learning Across Diverse Tabular Tasks

    Jun 29, 2026Marek Polewczyk, Maximilian Schambach, Marco Spinaci +2Tabular LearningTabular Data

  58. KnowsTFM: Knowledge-Informed Fine-Tuning of Small Tabular Foundation Models

    Jun 29, 2026Boshko Koloski, Xiangjian Jiang, Senja Pollak +3Tabular Foundation ModelsTabpfn

  59. Accelerometry-Derived Digital Biomarkers for Cardiometabolic Risk: A Population-Representative Tabular Benchmark with Uncertainty Quantification

    Jun 29, 2026Federico FelizziCardiometabolic RiskBiomarker

  60. Hierarchical Reinforcement Learning in StarCraft Micromanagement with Influence Maps and Cluster-based Scripts

    Jun 29, 2026Chunhui Bai, Changhe Li, Dequan Li +2Hierarchical Reinforcement LearningDeep Reinforcement Learning