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This paper identifies a mismatch between training (winner-take-all loss) and inference in trajectory forecasting models, leading to uninformative mode probabilities. It proposes post-hoc treatments using posterior-weighted merging and a one-step EM update to improve mode ranking and forecasting accuracy without retraining.