Super excited that TabICLv2 is out 🎉 🚀Beats RealTabPFN-2.5 with no tuning and purely synthetic pre-training data. 👉Introduces QASSMax for long-context generalization, early target embedding, repeated feature grouping, Muon, etc., and a much diversified synthetic data prior.

🎉 Announcing TabICLv2: State-of-the art Table Foundation Model, fast and open source A breakthrough for tabular ML: better prediction and faster runtime than alternatives, work by @JingangQu, @DHolzmueller, @MarineLeMorvan, and myself 👇

🚨Visit Jingang at our ICML poster later today if you are interested in - scaling tabular foundation models to larger datasets - open-source tabular foundation models - meta-learning in-context learning

TabICL offers two checkpoints: v1: Version in the paper, open-source pre-training code v1.1: Better, preview of upcoming work, same architecture, benchmarked in TabArena. Pre-training code not yet public. Outperforms TabPFNv2 for, roughly, >= 7,000 samples. Stay tuned for v2 😀

I’ll present "TabICL: A Tabular Foundation Model for In‑Context Learning on Large Data" at ICML 2025. 🗓 Tuesday, July 15, 2025 | 4:30–7:00 PM PDT 📍 East Exhibition Hall A‑B, Booth hashtag#E‑320 If you're curious about TabICL, come by the poster — I'd love to chat !