Zhenghang Xu — accepted AI-conference papers

2026

gDMC: A Generic Distributed Model Counting Framework via Work-Stealing

Zhenghang Xu, Minghao Yin, Junping Zhou, Jean-Marie Lagniez

IJCAI 2026

Propositional Model Counting (#SAT) is essential for probabilistic reasoning but faces scalability limits on single cores. Existing distributed approaches struggle with high initialization overheads (static decomposition) or precision loss and rigid architecture (dynamic solvers like dmc). We propos

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2022

An Exact Algorithm with New Upper Bounds for the Maximum k-Defective Clique Problem in Massive Sparse Graphs

Jian Gao, Zhenghang Xu, Ruizhi Li, Minghao Yin

AAAI 2022technical

The Maximum k-Defective Clique Problem (MDCP), as a clique relaxation model, has been used to solve various problems. Because it is a hard computational task, previous works can hardly solve the MDCP for massive sparse graphs derived from real-world applications. In this work, we propose a novel bra…

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