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Found 4 papers, 3 papers with code
AutoFT: Learning an Objective for Robust Fine-Tuning
Given a task, AutoFT searches for a fine-tuning procedure that enhances out-of-distribution (OOD) generalization.
Conservative Prediction via Data-Driven Confidence Minimization
Taking inspiration from this result, we present data-driven confidence minimization (DCM), which minimizes confidence on an uncertainty dataset containing examples that the model is likely to misclassify at test time.
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time
Temporal shifts -- distribution shifts arising from the passage of time -- often occur gradually and have the additional structure of timestamp metadata.
On Permutation Weights and $q$-Eulerian Polynomials
Weights of permutations were originally introduced by Dugan, Glennon, Gunnells, and Steingr\'imsson [2] in their study of the combinatorics of tiered trees.
Combinatorics 05A05
