Xiaomi-TabLDM: A Tabular Foundation Model Technical Report

arXiv:2609.03880 · cs.AI · Submitted 2026-09-03 · Read on arXiv

cs.AI

Submitted: 2026-09-03

Updated: 2026-09-04

Code: https://github.com/xiaomi-research/xiaomi-tabldm

Terminology

• Benchmark — 36× in this paper · explained in 2 episodes
• Foundation Model — 36× in this paper · explained in 3 episodes
• Foundation Models — 26× in this paper · explained in 7 episodes
• Embeddings — 15× in this paper · explained in 2 episodes
• Transformer — 14× in this paper · explained in 2 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• In-Context Learning — 10× in this paper · explained in 4 episodes
• AUC — 8× in this paper · explained in 2 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Robustness — 5× in this paper · explained in 5 episodes
• Topological Order — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Test-time Scaling — 4× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Mixture-of-Experts (MoE) — 2× in this paper · explained in 7 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Additivity — 1× in this paper · explained in 1 episode
• Causal Inference — 1× in this paper · explained in 4 episodes
• Core — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Hierarchical Classification — 1× in this paper · explained in 2 episodes
• In-Context Learning (ICL) — 1× in this paper · explained in 5 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Signal-to-noise ratio (SNR) — 1× in this paper · explained in 2 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Structural Causal Model (SCM) — 1× in this paper · explained in 4 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Xiaomi-TabLDM on the Balanced Comprehensive Challenging Omni-domain — 1× in this paper

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