Beyond Routine: A Controlled Benchmark of Event Grounding in Next-POI Prediction

Next-point-of-interest (next-POI) prediction forecasts a user’s next destination from their observed visit history. Events provide additional context, but predictive event utility does not necessarily imply event grounding. Context-on/off evaluation can reveal a gain without establishing whether it depends on the supported temporal and spatial bindings. We introduce BEYONDROUTINE, a controlled benchmark for event grounding in next-POI prediction under an event-aware input setting. Its construction combines chronological mobility records with independently documented events and requires evidence that event information was available before prediction. Events are matched to prediction instances without consulting the future target. Each comparison fixes the prediction instance, candidates, target, and trained model while removing event information or changing its time or location. We further introduce EventResidual, a reference predictor that factorizes history and event representations and applies gated, candidate-specific score corrections over shared POI representations. In the event-conditioned model study, the evaluated predictors show different utility and binding profiles, while stricter controls reveal additional variation in binding sensitivity. EventResidual shows positive paired point estimates on all three primary evaluation sets, including an event-utility difference of 0.0233 in MRR@10.