SPIN Unprocessed October 12, 2026 ai_technology research
Realism VS Accuracy: Event Sequence Forecasting from a Generative Modeling Perspective
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arXiv:2610.12586v1 Announce Type: new Abstract: Event sequences are chains of random events, each described by heterogeneous (numerical and categorical) features. The problem of event sequence forecasting occurs in finance, healthcare, business process intelligence, and other fields. In this work, we study multi-horizon forecasting of event sequences as a conditional generative modeling problem. We evaluate forecasts not only for prediction accuracy, but also for distributional realism. To this
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