Havana Rika

Learning to Rank: How GNNs Solve Max-Clique and Sparse PCA

Graph neural networks (GNNs) have shown promise on combinatorial problems such as Max-Clique, yet it remains unclear what algorithmic principles they actually learn. This paper introduces a concept-driven framework for evaluating and interpreting GNNs on such tasks. We begin with a principled benchm