Rankings are measured through the impact that each school's publications have made to the field of computer science.
Rankings are measured through the impact that each school's publications have made to the field of computer science.How can we measure quality of the publications? We believe that 1) The quality of research is best measured by peers in the same research area; 2) Careful use of LLMs can reveal the inherent quality measurements that the peers have already given by reading lots of papers. Hence, we developed a new ranking system where we analyze research papers from major AI conferences.For each paper, we ask a large language model (DeepSeek-R1-Distill-Llama-8B) what are the 5 most important papers to this paper. In other words, the five works that most strongly influence the study. By doing this, we trace which papers and authors are consistently seen as foundational to new discoveries.Next, we map these influential authors to their affiliated universities using the CSrankings name–affiliation database. Each time a paper is recognized as one of the "top five references" in another work, its authors and their institutions receive credit. To keep the scoring fair, points are divided by the number of co-authors, ensuring balanced recognition across collaborations.See the FAQ and the GitHub repository for any issues you may have.