AI RESEARCH
A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers
arXiv CS.AI
•
ArXi:2605.03391v1 Announce Type: cross Weighted first-order model counting (WFOMC) is a central task in lifted probabilistic inference: It asks for the weighted sum of all models of a first-order sentence over a finite domain. A long line of work has identified domain-liftable fragments of first-order logic, that is, syntactic classes for which WFOMC can be solved in time polynomial in the domain size. Among them, the two-variable fragment with counting quantifiers, $\mathbf{C}^2$, is one of the most expressive known liftable fragments.