Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems

ArXi:2603.24963v1 Announce Type: new Modern computational advertising platforms typically rely on recommendation systems to predict user responses, such as click-through rates, conversion rates, and other optimization events. To a wide variety of product surfaces and advertiser goals, these platforms frequently maintain an extensive ecosystem of machine learning (ML) models. However, operating at this scale creates significant development and efficiency challenges.