With the fast growing number of scientific papers produced every year, browsing through scientific literature can be a difficult task: formulating a precise query is not often possible if one is a novice in a given research field or different terms are often used to describe the same concept. To tackle some of these issues, we build a system based on topic models for browsing the arXiv repository. Through visualizing the relationship between keyphrases, documents and authors, the system allows the user to better explore the document search space compared to traditional systems based solely on query search. In this paper, we describe the design principles and the functionality supported by this system as well as report on a short user study.
