LLM-HYPER: Generative CTR Modeling For Cold-start Ad Personalization Via Llm-based Hypernetworks

Abstract

On online advertising platforms, newly introduced promotional ads face the cold-start problem, as they lack sufficient user feedback for model training. In this work, we propose LLM-HYPER, a novel framework that treats large language models (LLMs) as hypernetworks to directly generate the parameters of the click-through rate (CTR) estimator in a tra