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arXiv AI By Jules Kreuer, Sofiane Ouaari, Julia Hellmig, Julius Braitinger, Nico Pfeifer

TabBench-Bio: A Living Benchmark for Machine Learning on High-Dimensional Biomedical Tables

Read the original on arXiv AI →

TabBench-Bio is a living, interactive benchmark that evaluates machine learning models on 43 high‑dimensional biomedical tables, covering multiple domains. Using a shared cross‑validation protocol, the benchmark compares classical estimators, neural networks, and tabular foundation models across 28 feature‑by‑sample operating points, with RealTabPFN v2.5 achieving the highest performance at the reference cell of 10,000 features and 100 training samples. The benchmark provides reproducible results, fold‑level predictions, and invites community contributions to expand its dataset collection.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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