Cover Image

TabDPT: Scaling Tabular Foundation Models on Real Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ma, Junwei, Thomas, Valentin, Hosseinzadeh, Rasa, Labach, Alex, Kamkari, Hamidreza, Cresswell, Jesse C., Golestan, Keyvan, Yu, Guangwei, Caterini, Anthony L., Volkovs, Maksims
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Retrieval & Fine-Tuning for In-Context Tabular Models
by: Thomas, Valentin, et al.
Published: (2024)

TabPFGen -- Tabular Data Generation with TabPFN
by: Ma, Junwei, et al.
Published: (2024)

In-Context Data Distillation with TabPFN
by: Ma, Junwei, et al.
Published: (2024)

Generalization Can Emerge in Tabular Foundation Models From a Single Table
by: Ma, Junwei, et al.
Published: (2025)

Tabular Data Contrastive Learning via Class-Conditioned and Feature-Correlation Based Augmentation
by: Cui, Wei, et al.
Published: (2024)

RankJudge: A Multi-Turn LLM-as-a-Judge Synthetic Benchmark Generator
by: Tang, Zhenwei, et al.
Published: (2026)

A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
by: Kamkari, Hamidreza, et al.
Published: (2024)

Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections
by: Loaiza-Ganem, Gabriel, et al.
Published: (2024)

A Geometric Explanation of the Likelihood OOD Detection Paradox
by: Kamkari, Hamidreza, et al.
Published: (2024)

MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting
by: Du, Linfeng, et al.
Published: (2023)

Data-Efficient Multimodal Fusion on a Single GPU
by: Vouitsis, Noël, et al.
Published: (2023)

CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
by: Balazadeh, Vahid, et al.
Published: (2025)

A Geometric Framework for Understanding Memorization in Generative Models
by: Ross, Brendan Leigh, et al.
Published: (2024)

DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks
by: Cui, Wei, et al.
Published: (2025)

Self-supervised Representation Learning From Random Data Projectors
by: Sui, Yi, et al.
Published: (2023)

MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation
by: Gorti, Satya Krishna, et al.
Published: (2024)

Classifying and Addressing the Diversity of Errors in Retrieval-Augmented Generation Systems
by: Leung, Kin Kwan, et al.
Published: (2025)

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples
by: Vouitsis, Noël, et al.
Published: (2024)

Zero-Execution Retrieval-Augmented Configuration Tuning of Spark Applications
by: Suri, Raunaq, et al.
Published: (2025)

Learning Orthonormal Bases for Function Spaces
by: Kamkari, Hamidreza, et al.
Published: (2026)

Scaling Up Diffusion and Flow-based XGBoost Models
by: Cresswell, Jesse C., et al.
Published: (2024)

Trustworthy AI Must Account for Interactions
by: Cresswell, Jesse C.
Published: (2025)

TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields
by: Arazi, Alan, et al.
Published: (2025)

Order-based Structure Learning with Normalizing Flows
by: Kamkari, Hamidreza, et al.
Published: (2023)

El sistema penal en la encrucijada ante el reto de la inteligencia artificial
by: Mario Caterini
Published: (2022)

La ética económica y la responsabilidad penal
by: Mario Caterini
Published: (2015)

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data
by: Garg, Anurag, et al.
Published: (2025)

Aligning Dense Retrievers with LLM Utility via Distillation
by: Sandhu, Rajinder, et al.
Published: (2026)

TabQL: In-Context Q-Learning with Tabular Foundation Models
by: Liu, Qisai, et al.
Published: (2026)

MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
by: Sinodinos, Dimitrios, et al.
Published: (2025)

TabCF: Distributional Control Function Estimation with Tabular Foundation Models
by: Chen, Geping, et al.
Published: (2026)

OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale
by: Jiang, Dihong, et al.
Published: (2026)

TabFlex: Scaling Tabular Learning to Millions with Linear Attention
by: Zeng, Yuchen, et al.
Published: (2025)

IV-ICL: Bounding Causal Effects with Instrumental Variables via In-Context Learning
by: Balazadeh, Vahid, et al.
Published: (2026)

TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
by: Grinsztajn, Léo, et al.
Published: (2025)

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
by: Qu, Jingang, et al.
Published: (2025)

TabH2O: A Unified Foundation Model for Tabular Prediction
by: Pfeiffer, Pascal, et al.
Published: (2026)

Causal Foundation Models with Continuous Treatments
by: Stith, Christopher, et al.
Published: (2026)

On Convolutions, Intrinsic Dimension, and Diffusion Models
by: Leung, Kin Kwan, et al.
Published: (2025)

Interpretable Tabular Foundation Models via In-Context Kernel Regression
by: Miftachov, Ratmir, et al.
Published: (2026)