Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models
Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.
Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.
- Causilo tops TabArena single models with overall Elo 1794; 3rd of 88 with systems included
- Pretrained only on synthetic data; fit() stores context rows without updating weights
- Apache-2.0 code, research-only weights; commercial use requires separate Nums AI license
- Version 1.0.1 adds quantile regression outputs based on 999 native quantiles
- Fastest fit and predict versus TabICLv2 and TabPFN-3 on H100, using 8.15 GiB
From the original article
4 min read at marktechpost.com
Nums AI has released Causilo, a pretrained tabular foundation model for classification and regression with a scikit-learn interface. It posts the top TabArena Elo among single models, ahead of Google's TabFM and LG's EXAONE Tabular. The code is Apache-2.
By Michal Sutter · marktechpost.com
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