Xiaomi-TabLDM: A Tabular Foundation Model Technical Report
We introduce Xiaomi-TabLDM, a tabular large data foundation model for classification and regression via in-context learning, which delivers superior prediction accuracy without requiring task-specific fine-tuning. Pretrained exclusively on synthetic data generated from structural causal models (SCMs), our model enables more flexible context utilization and more efficient capacity scaling. i) A new performance standard. Strong regression performance across benchmarks: Xiaomi-TabLDM ranks 1st on OpenML-CTR23 and 2nd on regression across TALENT, TabArena, and BCCO, demonstrating consistently strong regression performance across four complementary benchmark suites. Favorable performance--effi...
| Authors | Xiaomi-TabLDM Team, :, Penghui Wang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 3 September 2026 |
| Last updated at source | 4 September 2026 |
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