Connected Papers is an innovative AI tool that visualizes academic research connections for enhanced discovery.

Connected Papers is a revolutionary AI-powered platform designed to transform academic research by mapping intricate relationships between scholarly papers. It provides users with dynamic visualizations of citation networks, significantly simplifying navigation through complex academic landscapes. The tool is exceptionally valuable for conducting comprehensive literature reviews, offering a holistic perspective on related works. To begin, users can input a paper's title, DOI, or arXiv ID, and the system will generate an interactive graph illustrating connected papers. This graph emphasizes the strength of relationships through citation metrics, enabling users to explore abstracts and access full texts where available. Among its standout features are 'Prior Works,' which pinpoints foundational papers in the field, and 'Derivative Works,' which highlights newer research influenced by the input paper. These functionalities empower researchers to grasp the historical context and latest advancements in their area of study. Connected Papers is user-friendly, requiring no technical expertise, and supports a wide range of disciplines including computer science, physics, biology, and social sciences. By optimizing academic discovery, it saves valuable time and delivers deeper insights into the interconnected nature of research, making it an essential tool for students, academics, and professionals.