urban-representation-learning

The paper introduces PRISM, a self-adjusting framework that adapts sparse MoE routing for region-specific multi-view fusion and uses a PID-inspired regulation mechanism to mitigate gradient conflicts in urban region representation learning, outperforming strong baselines on three large-scale urban datasets.