Ternary Gamma Semirings: From Neural Implementation to Categorical Foundations

ArXi:2603.19317v1 Announce Type: cross This paper establishes a theoretical framework connecting neural network learning with abstract algebraic structures. We first present a minimal counterexample nstrating that standard neural networks completely fail on compositional generalization tasks (0% accuracy). By