Connected Papers is an intelligent research assistant that transforms how scholars navigate academic literature. By employing sophisticated algorithms, it analyzes citation patterns to construct dynamic visual maps of paper relationships. Users begin by entering a paper identifier (title, DOI, or arXiv ID), and the system generates an interactive graph displaying the most relevant connected works. The visualization highlights both foundational prior works that influenced the field and recent derivative works that build upon the research. Each node in the graph represents a paper with key details, allowing users to quickly assess relevance through abstracts and access full texts when available. The platform supports comprehensive literature reviews by revealing hidden connections between papers across time, helping researchers identify seminal works and emerging trends. Special features include adjustable graph parameters to focus on specific connection strengths, timeline views to track idea evolution, and export options for integration with reference managers. Suitable for both broad exploratory research and targeted investigations, Connected Papers serves disciplines ranging from hard sciences to social sciences. Its intuitive interface requires no technical training, making complex citation analysis accessible to graduate students and senior researchers alike. The tool significantly reduces the time needed for comprehensive literature surveys while improving discovery of relevant materials that might otherwise remain overlooked in traditional search methods.