Ranking Step

Re-ranking is a post-processing step in information retrieval and recommendation systems that reorders an initial ranked list of items to better satisfy user needs, improving both precision and diversity. Current research focuses on integrating multimodal information (text and visuals), leveraging large language models (LLMs) for enhanced ranking, and developing efficient algorithms like those based on optimal transport or permutation-level interest modeling to handle large-scale datasets. These advancements are significantly impacting e-commerce search, question answering, and other applications by improving user experience and driving higher conversion rates or more accurate results.