Connected Papers is an advanced AI-powered platform designed to assist researchers, academics, and students in visualizing and exploring the intricate connections between academic papers. By analyzing citation networks and reference patterns, Connected Papers constructs a detailed visual graph that illustrates how papers are interrelated. This feature is particularly beneficial for individuals conducting literature reviews, as it offers a holistic view of the academic landscape surrounding a specific topic. To begin using Connected Papers, users can input the title, DOI, or arXiv ID of a paper they are interested in. The tool then generates an interactive graph showcasing the most relevant papers connected to the input paper, with the strength of their relationships indicated by citation metrics. Users can navigate the graph to explore various papers, view their abstracts, and, if available, download the full texts. Connected Papers also includes two specialized features: 'Prior Works,' which identifies seminal papers that have significantly shaped the field, and 'Derivative Works,' which highlights newer research that builds upon the input paper. These features make Connected Papers an essential resource for staying current with the latest developments and understanding the historical context of a topic. The platform is designed to be user-friendly, requiring no technical expertise, and is accessible to both experienced researchers and those new to academic exploration. Supporting a wide range of academic disciplines, including computer science, physics, biology, and social sciences, Connected Papers is a versatile tool that caters to diverse research needs. By simplifying the process of academic discovery, Connected Papers not only saves users time but also provides deeper insights into the interconnected nature of scholarly work, making it an invaluable asset for anyone engaged in academic research.