



Connected Papers leverages AI algorithms to create visual knowledge graphs, helping users discover related academic work beyond traditional citation methods. Researchers can visualize the connections between seminal and recent papers, identify gaps in literature, and generate bibliographies efficiently. The platform allows multi-origin graph comparisons for cross-disciplinary exploration and integrates seamlessly with arXiv, Semantic Scholar, and PubMed. Interactive nodes provide detailed paper information, while downloadable bibliographies simplify citation management. With a freemium model and intuitive interface, Connected Papers empowers students, educators, librarians, and professionals to explore research landscapes, track trends, and stay informed about relevant academic advancements.
Key Features
Visual Knowledge Graphs – Cluster papers by similarity for intuitive exploration
Similarity-Based Organization – Connect papers via co-citation and bibliographic coupling
Prior and Derivative Works – Identify foundational and recent works in the field
Multi-Origin Graphs – Compare multiple papers to find intersecting research areas
Integration with Research Tools – Supports arXiv, Semantic Scholar, and PubMed inputs
Comprehensive Bibliography Creation – AI-assisted suggestions to fill literature gaps
User-Friendly Interface – Expandable nodes, interactive exploration, downloadable bibliographies
Industries
Academia & Research Institutions
Education & E-Learning
Libraries & Information Services
R&D & Industry Research
Policy Analysis & Government Research