| A Suite of Fairness Datasets for Tabular Classification | Jul 31, 2023 | ClassificationFairness | —Unverified | 0 |
| Tokenize features, enhancing tables: the FT-TABPFN model for tabular classification | Jun 11, 2024 | Classificationtabular-classification | —Unverified | 0 |
| Metalearning Using Structure-rich Pipeline Representations for Better AutoML | Mar 13, 2021 | AutoMLreinforcement-learning | —Unverified | 0 |
| PTab: Using the Pre-trained Language Model for Modeling Tabular Data | Sep 15, 2022 | Language ModelingLanguage Modelling | —Unverified | 0 |
| Quantifying Prediction Consistency Under Fine-Tuning Multiplicity in Tabular LLMs | Jul 4, 2024 | Decision Makingtabular-classification | —Unverified | 0 |
| Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications | Oct 23, 2023 | FairnessIn-Context Learning | —Unverified | 0 |
| Is margin all you need? An extensive empirical study of active learning on tabular data | Oct 7, 2022 | Active LearningAll | —Unverified | 0 |
| TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems | Feb 4, 2025 | Computational EfficiencyIn-Context Learning | —Unverified | 0 |
| Learning Interpretable Differentiable Logic Networks for Tabular Regression | May 29, 2025 | Computational Efficiencyregression | —Unverified | 0 |
| The Disagreement Problem in Faithfulness Metrics | Nov 13, 2023 | BenchmarkingExplainable artificial intelligence | —Unverified | 0 |
