4 citations · 15 across the 15 of their papers we have counts for
26 papers
Unary Functions, Automorphisms, and Unlabeled First-Order Model Counting
Ondřej Kuželka
Every fixed first-order sentence determines an enumerative sequence , counting its models on the labeled domain . We study the complexity of th…
Weighted First-Order Model Counting over Ordered Domains
Jan Tóth, Qipeng Kuang, Kuncheng Zou +4
The Weighted First-Order Model Counting Problem (WFOMC) asks for the weighted sum of models of a first-order logical sentence over a domain. It is a fundamental problem in statisti…
Parallel Noising in Neural Markov Logic Networks
Peter Jung, Giuseppe Marra, Ondrej Kuzelka
Neural Markov Logic Networks (NMLNs) are a flexible neurosymbolic relational model. Previous work has shown that, although NMLNs achieve strong performance as generative models for…
CombEval: A Framework for Evaluating Combinatorial Counting in Large Language Models
Yuxu Zhou, Ondřej 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…
A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers
Shixin Sun, Astrid Klipfel, Ondřej 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…
Tractable Weighted First-Order Model Counting with Bounded Treewidth Binary Evidence
Václav Kůla, Qipeng Kuang, Yuyi Wang +2
The Weighted First-Order Model Counting Problem (WFOMC) asks to compute the weighted sum of models of a given first-order logic sentence over a given domain. Conditioning WFOMC on…