11 papers
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…
Verifiable Counterfactual Supervision for Process Reward Models
Yinghui Chi, Yuanhong Wang
Process reward models (PRMs) require supervision that identifies not only whether a reasoning trajectory is correct, but also where the reasoning process first becomes unsupported…
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…
Solving Combinatorial Counting Problems with Weighted First-Order Model Counting
Yuanhong Wang, Juhua Pu, Yuxu Zhou +2
Combinatorial counting problems pervade artificial intelligence, statistics, and discrete mathematics. Whether the task is enumerating subsets, multisets, permutations, partitions,…
On Knowledge Compilation For Two-Variable First-Order Logic
Qiaolan Meng, Juhua Pu, Hongting Niu +3
Knowledge compilation transforms logical theories into circuit representations that support efficient reasoning. We study this problem for propositional groundings of FO2, the two-…
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…