Document Ranking

Document ranking aims to order documents by their relevance to a given query, a crucial task in information retrieval. Current research focuses on improving the efficiency and accuracy of ranking algorithms, exploring both traditional methods like query likelihood models and novel approaches leveraging large language models (LLMs) through techniques such as pairwise ranking prompting and tournament-style strategies. These advancements are driving improvements in search engine performance, enabling more effective systematic reviews in fields like medicine, and facilitating faster processing of large-scale text corpora.