AINeutralarXiv – CS AI · 15h ago6/10
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LUCoS: Latent Unsupervised Context Selection for Tabular Foundation Models
Researchers introduce LUCoS, an unsupervised method for selecting training instances in tabular machine learning that uses latent embeddings rather than raw features. The approach significantly outperforms random selection across 67 datasets, addressing a critical cold-start problem in tabular foundation models like TabPFN.