A GNN-encoded flow matching model learns to generate STL-satisfying trajectories across five robot simulation domains, with a 200K-specification dataset, reporting best-of-1024 satisfaction rates.
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TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matching
A GNN-encoded flow matching model learns to generate STL-satisfying trajectories across five robot simulation domains, with a 200K-specification dataset, reporting best-of-1024 satisfaction rates.