Average-Case Hardness of Parity Problems: Orthogonal Vectors, k-SUM and More
Abstract
This work establishes conditional lower bounds for average-case {\em parity}-counting versions of the problems -XOR, -SUM, and -OV. The main contribution is a set of self-reductions for the problems, providing the first specific distributions, for which: is average-case hard, under the -OV hypothesis (and hence under SETH), is average-case hard, under the -SUM hypothesis, and is average-case hard, under the -XOR hypothesis. Under the very believable hypothesis that at least one of the -OV, -SUM, -XOR or -Clique hypotheses is true, we show that parity--XOR, parity--SUM, and parity--OV all require at least (and sometimes even more) time on average (for specific distributions). To achieve these results, we present a novel and improved framework for worst-case to average-case fine-grained reductions, building on the work of Dalirooyfard, Lincoln, and Vassilevska Williams, FOCS 2020.
Cite
@article{arxiv.2503.21951,
title = {Average-Case Hardness of Parity Problems: Orthogonal Vectors, k-SUM and More},
author = {Mina Dalirrooyfard and Andrea Lincoln and Barna Saha and Virginia Vassilevska Williams},
journal= {arXiv preprint arXiv:2503.21951},
year = {2025}
}
Comments
in SODA 2025