An adaptive-trunk DeepONet framework predicts localized structural responses in long-span bridges with high accuracy. By using distance-aware features and a stiffness-informed Schur complement, it achieves FEM-level accuracy with less than 5% error, reducing total response evaluation time by 60x and inference speed by up to four orders of magnitude compared to finite element methods.