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This paper presents an exploratory benchmark for detecting sparse-ring fraud in dynamic transaction graphs using quantum-inspired Contextual Machine Learning (CML) compared to a GRU baseline, finding that hybrid graph features combining identity-preserving and topological summaries yield the best results.