CRUMB speeds up PFN inference on large tabular datasets by clustering queries and selecting MMD-matched context subsets, outperforming prior selection methods on the 51-dataset TabArena benchmark across three architectures while handling covariate drift.
In-context data distillation with tabpfn
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A new constrained parametric bootstrap test for single-population ancestry in the supervised admixture model, proven to have asymptotic level alpha and consistency.
VIP-COP is a black-box method that optimizes context for tabular foundation models by ranking and selecting high-value samples and features via online KernelSHAP regression, outperforming baselines on large high-dimensional data.
citing papers explorer
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CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching
CRUMB speeds up PFN inference on large tabular datasets by clustering queries and selecting MMD-matched context subsets, outperforming prior selection methods on the 51-dataset TabArena benchmark across three architectures while handling covariate drift.
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Testing for Single-Population Ancestry in the Admixture Model
A new constrained parametric bootstrap test for single-population ancestry in the supervised admixture model, proven to have asymptotic level alpha and consistency.
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VIP-COP: Context Optimization for Tabular Foundation Models
VIP-COP is a black-box method that optimizes context for tabular foundation models by ranking and selecting high-value samples and features via online KernelSHAP regression, outperforming baselines on large high-dimensional data.