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PAPERQA
Superhuman RAG for scientific literature with cited, grounded answers
Apache-2.0
ABOUT
Researchers and knowledge workers struggle to efficiently extract accurate, cited answers from large collections of scientific papers and technical documents. PaperQA solves this with a multi-step agent that automatically searches across documents, retrieves relevant passages, ranks evidence, and synthesizes well-cited answers — achieving superhuman accuracy on scientific QA benchmarks like LitQA2.
INSTALL
pip install paper-qaINTEGRATION GUIDE
1. Automate literature reviews with cited evidence extracted from scientific papers
2. Answer domain-specific research questions with grounded citations from primary sources
3. Fact-check scientific claims against published literature at superhuman accuracy
4. Build knowledge management systems for R&D teams working with technical documents
TAGS
ragscientific-researchdocument-qaliterature-reviewpython