TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Fuente:
arXiv
Saved in:
| Main Authors: | Tschalzev, Andrej, Erickson, Nick, Wang, Yuyang, Rangwala, Huzefa, Lüdtke, Stefan, Stuckenschmidt, Heiner, Bartelt, Christian |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data
by: Tschalzev, Andrej, et al.
Published: (2024)
by: Tschalzev, Andrej, et al.
Published: (2024)
Unreflected Use of Tabular Data Repositories Can Undermine Research Quality
by: Tschalzev, Andrej, et al.
Published: (2025)
by: Tschalzev, Andrej, et al.
Published: (2025)
Explaining Neural Networks without Access to Training Data
by: Marton, Sascha, et al.
Published: (2022)
by: Marton, Sascha, et al.
Published: (2022)
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods
by: Tschalzev, Andrej, et al.
Published: (2024)
by: Tschalzev, Andrej, et al.
Published: (2024)
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data
by: Marton, Sascha, et al.
Published: (2023)
by: Marton, Sascha, et al.
Published: (2023)
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent
by: Marton, Sascha, et al.
Published: (2023)
by: Marton, Sascha, et al.
Published: (2023)
TabArena: A Living Benchmark for Machine Learning on Tabular Data
by: Erickson, Nick, et al.
Published: (2025)
by: Erickson, Nick, et al.
Published: (2025)
Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
by: Marton, Sascha, et al.
Published: (2024)
by: Marton, Sascha, et al.
Published: (2024)
FeatNavigator: Automatic Feature Augmentation on Tabular Data
by: Liang, Jiaming, et al.
Published: (2024)
by: Liang, Jiaming, et al.
Published: (2024)
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications
by: Salinas, David, et al.
Published: (2023)
by: Salinas, David, et al.
Published: (2023)
CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
by: Gastinger, Julia, et al.
Published: (2025)
by: Gastinger, Julia, et al.
Published: (2025)
Reevaluation of Inductive Link Prediction
by: Ott, Simon, et al.
Published: (2024)
by: Ott, Simon, et al.
Published: (2024)
Protein Structure Tokenization: Benchmarking and New Recipe
by: Yuan, Xinyu, et al.
Published: (2025)
by: Yuan, Xinyu, et al.
Published: (2025)
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification
by: Han, Xiaoxue, et al.
Published: (2024)
by: Han, Xiaoxue, et al.
Published: (2024)
DispaRisk: Auditing Fairness Through Usable Information
by: Vasquez, Jonathan, et al.
Published: (2024)
by: Vasquez, Jonathan, et al.
Published: (2024)
TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments
by: Cheng, Zi-Jian, et al.
Published: (2025)
by: Cheng, Zi-Jian, et al.
Published: (2025)
Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models
by: Zhang, Xiyuan, et al.
Published: (2025)
by: Zhang, Xiyuan, et al.
Published: (2025)
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners
by: Kong, Kezhi, et al.
Published: (2024)
by: Kong, Kezhi, et al.
Published: (2024)
Disentangling Exploration of Large Language Models by Optimal Exploitation
by: Grams, Tim, et al.
Published: (2025)
by: Grams, Tim, et al.
Published: (2025)
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space
by: Zhang, Hengrui, et al.
Published: (2023)
by: Zhang, Hengrui, et al.
Published: (2023)
TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
by: Rubachev, Ivan, et al.
Published: (2024)
by: Rubachev, Ivan, et al.
Published: (2024)
Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens
by: Cen, Zhepeng, et al.
Published: (2024)
by: Cen, Zhepeng, et al.
Published: (2024)
Fact Probability Vector Based Goal Recognition
by: Wilken, Nils, et al.
Published: (2024)
by: Wilken, Nils, et al.
Published: (2024)
History repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting
by: Gastinger, Julia, et al.
Published: (2024)
by: Gastinger, Julia, et al.
Published: (2024)
PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances
by: Elyasi, Keyvan Amiri, et al.
Published: (2024)
by: Elyasi, Keyvan Amiri, et al.
Published: (2024)
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer
by: Pengmei, Zihan, et al.
Published: (2024)
by: Pengmei, Zihan, et al.
Published: (2024)
TabPFGen -- Tabular Data Generation with TabPFN
by: Ma, Junwei, et al.
Published: (2024)
by: Ma, Junwei, et al.
Published: (2024)
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs
by: Wang, Zifeng, et al.
Published: (2023)
by: Wang, Zifeng, et al.
Published: (2023)
A Divide-and-Conquer Approach for Modeling Arrival Times in Business Process Simulation
by: Kirchdorfer, Lukas, et al.
Published: (2025)
by: Kirchdorfer, Lukas, et al.
Published: (2025)
Relatron: Automating Relational Machine Learning over Relational Databases
by: Chen, Zhikai, et al.
Published: (2026)
by: Chen, Zhikai, et al.
Published: (2026)
A*Net and NBFNet Learn Negative Patterns on Knowledge Graphs
by: Betz, Patrick, et al.
Published: (2024)
by: Betz, Patrick, et al.
Published: (2024)
TabAttackBench: A Benchmark for Adversarial Attacks on Tabular Data
by: He, Zhipeng, et al.
Published: (2025)
by: He, Zhipeng, et al.
Published: (2025)
Rethinking BPS: A Utility-Based Evaluation Framework
by: Özdemir, Konrad, et al.
Published: (2025)
by: Özdemir, Konrad, et al.
Published: (2025)
Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
by: Wang, Yingheng, et al.
Published: (2024)
by: Wang, Yingheng, et al.
Published: (2024)
From Demonstrations to Rewards: Alignment Without Explicit Human Preferences
by: Zeng, Siliang, et al.
Published: (2025)
by: Zeng, Siliang, et al.
Published: (2025)
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
by: Si, Jacob, et al.
Published: (2024)
by: Si, Jacob, et al.
Published: (2024)
fev-bench: A Realistic Benchmark for Time Series Forecasting
by: Shchur, Oleksandr, et al.
Published: (2025)
by: Shchur, Oleksandr, et al.
Published: (2025)
Federated Learning for Tabular Data using TabNet: A Vehicular Use-Case
by: Lindskog, William, et al.
Published: (2024)
by: Lindskog, William, et al.
Published: (2024)
AutoG: Towards automatic graph construction from tabular data
by: Chen, Zhikai, et al.
Published: (2025)
by: Chen, Zhikai, et al.
Published: (2025)
Inference-Time Refinement Closes the Synthetic-Real Gap in Tabular Diffusion
by: Lomurno, Eugenio, et al.
Published: (2026)
by: Lomurno, Eugenio, et al.
Published: (2026)
Similar Items
-
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data
by: Tschalzev, Andrej, et al.
Published: (2024) -
Unreflected Use of Tabular Data Repositories Can Undermine Research Quality
by: Tschalzev, Andrej, et al.
Published: (2025) -
Explaining Neural Networks without Access to Training Data
by: Marton, Sascha, et al.
Published: (2022) -
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods
by: Tschalzev, Andrej, et al.
Published: (2024) -
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data
by: Marton, Sascha, et al.
Published: (2023)