What Do Tabular Foundation Models Compute In Context? In-Situ Representation Refinement through Attention-Gated Updates

arXiv:2609.27679 · cs.LG · Submitted 2026-09-23 · Read on arXiv

cs.LG

Submitted: 2026-09-23

Updated: 2026-09-25

Terminology

• Accuracy — 64× in this paper · explained in 1 episode
• Benchmark — 31× in this paper · explained in 2 episodes
• AUC — 24× in this paper · explained in 2 episodes
• Foundation Model — 9× in this paper · explained in 3 episodes
• Transformer — 8× in this paper · explained in 2 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• In-Context Learning — 3× in this paper · explained in 4 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Allocator — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Recommendation — 1× in this paper · explained in 2 episodes

Sources

• EXAONE Tabular 1.0 : Technical Report
• TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
• TabPFN-3: Technical Report
• TabICLv2: A better, faster, scalable, and open tabular foundation model

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