3 papers
cs.AI2026
CombEval: A Framework for Evaluating Combinatorial Counting in Large Language Models
Yuxu Zhou, OndÅej Kuželka, Yuyi Wang +2
We present CombEval, a dynamic benchmark for evaluating combinatorial counting in large language models. CombEval represents each problem as a typed Cofola specification over entit…
cs.LO2026
A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers
Shixin Sun, Astrid Klipfel, OndÅej Kuželka +2
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…
cs.AI2025
Faster Lifting for Ordered Domains with Predecessor Relations
Kuncheng Zou, Jiahao Mai, Yonggang Zhang +4
We investigate lifted inference on ordered domains with predecessor relations, where the elements of the domain respect a total (cyclic) order, and every element has a distinct (cl…