Classifying unsafe ad content has proven an enticing problem space for leveraging large language models (LLMs). The inherent complexity involved in identifying policy-violating content demands solutions capable of deep contextual and cultural understanding, areas of relative strength for LLMs over traditional machine learning systems. But fine-tuning LLMs for such complex tasks requires high-fidelity training data that is difficult and expensive to curate at the necessary quality and scale. S...
