Beats tuned baseline
2026
Displacement-Huber distribution pooling
Replace ordinary Wasserstein or arithmetic pooling of distribution-valued features with a barycenter whose individual quantile displacements are Huberized. Small changes between input distributions remain averaged quadratically, while a corrupted token, expert, graph neighborhood, or augmentation cannot move the pooled distribution arbitrarily far. The module is especially cheap for one-dimensional distributions represented by fixed quantile vectors.
Paper: Huber-Wasserstein barycenters for robust distribution-valued data
arXiv:2608.13131