Meng-Zi Tang

Do We Really Need LLMs to Augment All? A Selective Augmentation Framework with Lightweight Language Models for Multimodal CTR Prediction

In recent years, multimodal models and large language models (LLMs) have been increasingly applied to click-through rate (CTR) prediction, owing to their ability to extract recommendation-relevant information from raw content and thereby alleviate the long-standing issue of collaborative signal sparsity. Existing parad...