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cs.LG2025
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Yang Li, Jinpei Guo, Runzhong Wang +2
Diffusion models have recently advanced Combinatorial Optimization (CO) as a powerful backbone for neural solvers. However, their iterative sampling process requiring denoising acr…
cs.LG2023★ 1 cited
G4SATBench: Benchmarking and Advancing SAT Solving with Graph Neural Networks
Zhaoyu Li, Jinpei Guo, Xujie Si
Graph neural networks (GNNs) have recently emerged as a promising approach for solving the Boolean Satisfiability Problem (SAT), offering potential alternatives to traditional back…