Neural Tractability via Structure: Learning-Augmented Algorithms for Graph Combinatorial Optimization

Neural solvers provide fast solutions to graph combinatorial optimization problems, but training alone does not guarantee solution quality. Exact methods guarantee optimality but can be prohibitively expensive. We propose Neural Fixed-Parameter Tractable (N-FPT), a neural-model-agnostic framework th