Connected Papers is an AI-powered research tool that helps academics, scientists, and students explore connections between academic papers through visual citation mapping. Unlike traditional search engines, it analyzes citation networks and semantic similarities to generate interactive graphs, allowing researchers to discover related work, trace research trends, and identify influential studies. This makes it an excellent tool for conducting literature reviews, finding key papers, and uncovering emerging research areas.

Connected Papers enables users to input a single paper, and the AI will generate a graph of closely related studies based on citation patterns and thematic similarities. This visual approach helps researchers identify foundational works, spot knowledge gaps, and follow the evolution of research topics. The platform is especially useful for interdisciplinary research, where citation patterns may not be as obvious through conventional searches.

Connected Papers offers a free version that allows users to explore citation maps and discover related research, but advanced features, such as expanded networks and enhanced filtering, require a paid plan (~$8/month). API access is not widely advertised, making it primarily a standalone research tool rather than an integration for external platforms.

Connected Papers is a valuable AI tool for academic research that simplifies literature discovery by visually mapping research connections. With its AI-powered citation analysis, intuitive interface, and structured approach to paper discovery, it is an indispensable resource for researchers conducting deep literature reviews. While the free version is useful for basic exploration, paid plans unlock more extensive mapping capabilities for advanced research.