Author

Benjamin J. Zhang

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#machine learning May 2026

ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks

This work introduces ISOMORPH, the first public digital twin of a multi-echelon logistics network with interpretable, user-configurable parameters and modular topology, demand, and control rules, and introduces forecasting regimes that differ from standard real-world TSF benchmarks.

Zhizhen Zhang, Hyemin Gu, Benjamin J. Zhang et al. · arXiv.org · 0 citations

#artificial intelligence Preprint Sep 2026

When Should a World Model Move? Loss-Conditioned State Execution

We introduce loss-conditioned state execution, a model-agnostic method that decides whether to execute a world model's fixed feasible proposal or retain the current state. Predictive informativeness alone, however, does not establish whether an update will reduce downstream loss. Occurrence ranking can approach perfect...

Jin-Tao Xu, Zheng-Yu Chen, Benjamin J. Zhang et al. · 0 citations