Yunchun Su

HIVE: Hierarchical Generation of Integrated and Varied Ensembles for Efficient Out-of-Distribution Generalization

Out-of-distribution (OOD) generalization in industrial Model-as-a-Service (MaaS) systems is often hindered by a trilemma of heterogeneous distribution shifts, strict inference latency budgets, and rigorous privacy constraints. Traditional robust learning and emerging foundation models frequently struggle with the entan...