Revisiting Graph Representations for ML-Based Binary Code Similarity Detection: A Systematic Study
A systematic study of graph representations for ML-based BCSD is presented, finding that no single representation is universally dominant, that distinct topologies exhibit unique strengths depending on the evaluation scenario, and that their rankings are largely backbone-stable despite varying absolute performance.