Connected Papers is a powerful AI-driven tool designed to help researchers, academics, and students explore and visualize the relationships between academic papers. By analyzing citations and references, Connected Papers creates a visual graph that maps out the connections between papers, making it easier to identify key works, trace the evolution of ideas, and discover relevant literature in a specific field. The tool is particularly useful for those conducting literature reviews, as it provides a comprehensive overview of the academic landscape surrounding a particular topic. To use Connected Papers, users simply input the title, DOI, or arXiv ID of a paper of interest. The tool then generates a graph that displays the most relevant papers connected to the input paper, highlighting the strength of their relationships based on citation patterns. Users can interact with the graph to explore different papers, access their abstracts, and even download the full texts if available. Connected Papers also offers a 'Prior Works' feature, which identifies foundational 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 invaluable resource for staying up-to-date with the latest research and understanding the historical context of a topic. Additionally, Connected Papers supports multiple academic disciplines, including computer science, physics, biology, and social sciences, making it a versatile tool for a wide range of users. The platform is user-friendly and requires no technical expertise, making it accessible to both seasoned researchers and those new to academic research. Overall, Connected Papers streamlines the process of academic discovery, saving users time and effort while providing deeper insights into the interconnectedness of scholarly work.