Connected Papers is an advanced AI-powered platform tailored for researchers, academics, and students to visualize and explore the intricate connections between academic papers. By analyzing citations and references, it constructs a detailed visual graph that maps the relationships between papers, simplifying the process of identifying pivotal works, tracing the development of ideas, and discovering pertinent literature in a specific domain. This tool is especially beneficial for those engaged in literature reviews, as it offers a holistic view of the academic terrain surrounding a particular subject. To utilize Connected Papers, users simply enter the title, DOI, or arXiv ID of a paper of interest. The tool then generates a graph showcasing the most relevant papers connected to the input paper, emphasizing the strength of their relationships based on citation patterns. Users can interact with the graph to explore various papers, access their abstracts, and even download the full texts if available. Connected Papers also includes a 'Prior Works' feature, which identifies seminal papers that have significantly influenced the field, and a 'Derivative Works' feature, which highlights newer papers that build upon the input paper. This makes it an essential resource for staying current with the latest research and understanding the historical context of a topic. Furthermore, Connected Papers supports multiple academic disciplines, including computer science, physics, biology, and social sciences, making it a versatile tool for a broad spectrum of users. The platform is user-friendly and requires no technical expertise, making it accessible to both experienced researchers and those new to academic research. Overall, Connected Papers enhances the process of academic discovery, saving users time and effort while providing deeper insights into the interconnectedness of scholarly work.