Future-House/paper-qa
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High accuracy RAG for answering questions from scientific documents with citations
10 mentions on Hacker News by 4 people: 2 stories, 8 comments · first 2024-09-11 · latest 2025-03-05
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We measured PaperQA2 ( https://github.com/Future-House/paper-qa ) against the science portion of the RAG-Arena benchmark ( https://arxiv.org/abs/2407.13998 ), it's the first time we've compared PaperQA2 against other systems based on…
comment by mskar · 2025-03-05 · in PaperQA2 tops the RAG-QA Arena science benchmark -
…I’ve had similar findings! LLM based “document-chunk” ranking is a core feature of PaperQA2 ( https://github.com/Future-House/paper-qa ) and part of why it works so well for scientific Q&A compared to traditional embedding-ranking based…
comment by mskar · 2025-02-25 · in Hard problems that reduce to document ranking -
…and https://news.ycombinator.com/item?id=42871143 ), and some cool projects like https://github.com/Future-House/paper-qa?tab=readme-ov-file#... are using PyMuPDF. My experience with Tesseract is pretty sad, it's usually not good enough an
comment by eamag · 2025-02-15 · in Show HN: Kreuzberg – Modern async Python library for document text extraction -
…is awesome! If you’re interested, you could add a search tool client for your backend in paper-qa ( https://github.com/Future-House/paper-qa ). Then paper-qa users would be able to use your semantic search as part of its workflow.
comment by mskar · 2024-12-25 · in Show HN: I made a website to semantically search ArXiv papers -
Github: https://github.com/Future-House/paper-qa
comment by handfuloflight · 2024-11-14 · in Language agents achieve superhuman synthesis of scientific knowledge -
We used an open-source AI RAG library, PaperQA2 ( https://github.com/Future-House/paper-qa ), to generate well cited articles for every gene in the human genome, ~15k of which had no existing prior articles. In terms of factuality, we…
comment by mskar · 2024-10-23 · in WikiCrow: An article for every human gene -
We're sharing some experiments in designing RAG systems via the open source PaperQA2 system ( https://github.com/Future-House/paper-qa ). PaperQA2's design is interesting because it isn't concerned with cost, so it uses expensive…
comment by mskar · 2024-09-19 · in Exchanging more frontier LLM compute for higher accuracy in RAG systems -
We are announcing PaperQA2 ( https://github.com/Future-House/paper-qa ), the first AI agent to achieve superhuman performance on a variety of different scientific literature search tasks. PaperQA2 is an agent optimized for retrieving and…
comment by mskar · 2024-09-11 · in PaperQA2: Superhuman Scientific Literature Search