AI-powered research tool providing evidence-backed answers from millions of peer-reviewed papers, with copilot, library, and smart filtering.
PaperLens is an AI-powered research tool that provides evidence-backed answers grounded in millions of peer-reviewed papers from sources like arXiv, Crossref, and Semantic Scholar. It offers features such as research answers with evidence strength and consensus, a research copilot for follow-up questions and paper deep-dives, the ability to save and generate structured wiki summaries for papers, and smart filtering by date, quality, and source. The tool is designed to help researchers find, understand, and organize scientific literature faster.
Key Features
check_circleResearch answers with evidence strength and consensus
check_circleResearch copilot for follow-up questions and deep-dives
check_circleSave papers and generate structured wiki summaries
check_circleFilter by date, quality, and source
check_circleSemantic search
check_circleReal-time web search
check_circleBuild library
check_circleLatest AI models for analysis
Use Cases
lightbulbGraduate students quickly find evidence-backed answers for their literature review, reducing hours of manual searching to seconds.
lightbulbResearchers verify claims by cross-referencing multiple peer-reviewed papers, ensuring their work is grounded in credible science.
lightbulbScientists stay up-to-date with the latest findings by filtering papers by date and quality, surfacing only the most relevant research.
lightbulbAcademic teams collaborate on projects by saving papers and generating structured summaries, streamlining knowledge sharing.
lightbulbJournalists fact-check scientific claims by querying PaperLens for consensus and limitations across millions of papers.
lightbulbPolicy makers gather evidence on topics like climate change or public health, using AI-summarized findings to inform decisions.
lightbulbPhD candidates organize their reading by building a personal library of papers with auto-generated wiki-style breakdowns.
