LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence https://arxiv.org/abs/2609.17488
RelBench: Relational Deep Learning Benchmark
Minimal, fast + educational reimplementation of the TabICLv2 architecture + prior
TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
The Relational Transformer architecture for Relational Foundation Models
🚀 Awesome TabPFN use-cases from around the world
(ICML 2026) GraphPFN: A Prior-Data Fitted Graph Foundation Model
Turning Tabular Foundation Models into Graph Foundation Models
A curated collection of research on tabular foundation models: models pretrained on large-scale (synthetic) data that generalize to unseen tabular tasks at inference time.
TabCausal: Pretraining Across Causal Environments for Tabular Causal Discovery
Tabular Foundation Models Adaptation for Survival Analysis
Discovering association rules from high dimensional small tabular data via neurosymbolic rule mining supported by fine-tuning using tabular foundation models
The official implementation for the paper, “Clustering Method for Tabular Data Based on Pretrained Foundation Models with Synthetic Data.”
Can domain knowledge be encoded in a tabular foundation model's pretraining prior? TabICL prior design for credit-risk PD and LGD.
Exploration of tabular data foundation models
[QDB'25] Out in the wild of modern data science, good tabular AI meets bad data. Who wins?
Benchmarking Synthefy's Nori V1 tabular foundation model (in-context learning, zero training) against sklearn baselines
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