citrus search

citrus search is a specialized academic search engine that helps researchers find closely related scientific papers through similarity-based searching. Instead of using traditional text queries that often return many false positives, you start with a seed paper you already know is relevant, and citrus search finds publications that share meaningful connections through citation patterns or content similarities.

The tool offers two distinct search methods: citation network analysis finds papers with similar connections in academic citation graphs, while content-based search identifies papers discussing similar concepts and research questions in their abstracts and titles. Both approaches use machine learning techniques to compute paper similarities, drawing from Semantic Scholar's massive Open Research Corpus containing over 200 million publications and approximately 2 billion citations.

Researchers, academics, and students benefit most from citrus search when conducting literature reviews, exploring new research areas, or ensuring they haven't missed important papers that might use different terminology. The visual timeline overview helps users quickly grasp the landscape of related work and identify key contributions in their field of study.