OrionMoE-v1.0: A Mixture-of-Experts Foundation Model for Tabular In-Context Learning
cs.LG, cs.AI
Submitted: 2026-10-14
Updated: 2026-10-18
Code: https://github.com/Lexsi-Labs/OrionMoE
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- TabPFN-3: Technical Report
- TabPFN-3.5: Technical Report
- TabICLv2: A better, faster, scalable, and open tabular foundation model
- Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning
- Orion-Bix: Bi-Axial Attention for Tabular In-Context Learning
- LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence
- LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence
- EXAONE Tabular 1.0 : Technical Report
- TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
- TabArena: A Living Benchmark for Machine Learning on Tabular Data
- Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
- Shaping the Prior: How Synthetic Task Distributions Determine Tabular Foundation Model Quality
- OpenML Benchmarking Suites
- Xiaomi-TabLDM: A Tabular Foundation Model Technical Report
- Beyond IID: How General Are Tabular Foundation Models, Really?
- Causilo Technical Report
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