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  This dataset tracks which scientific papers are most often cited by **Asta**, an agentic research platform that uses retrieval-augmented generation (RAG) to answer scientific questions. Each record corresponds to a citation event in Asta's *Summarize Literature* tool, showing which papers the system retrieved and cited across more than **113,000 user queries**, **four million citations** to over **two million distinct papers**.
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  By making these data public, we aim to create a transparent, trackable measure of which research most directly powers AI-generated answers—helping ensure that scientific contributions are visible and credited in the AI era.
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- We release this dataset under the **Open Data Commons Attribution License (ODC-By 1.0)**. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use). Weekly updates reflect ongoing usage patterns as Asta continues to evolve. We invite researchers, bibliometricians, and AI developers to explore citation dynamics across fields, assess how AI systems surface influential work, and help build a future where credit and accountability are integral to AI-assisted discovery.
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  The most recent update to the data can always be retrieved using the 'latest' config:
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  ## Dataset Details
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  - **Dataset name:** Asta Summary Citation Counts
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  - **Maintainer:** Allen Institute for AI (AI2)
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- - **License and Use:** Released under [ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) and intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).
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  - **Update frequency:** Weekly
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  - **Source platform:** Asta (https://asta.ai)
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  - **Primary use cases:** bibliometrics, AI transparency, citation dynamics, evaluation of retrieval-augmented generation systems
 
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  This dataset tracks which scientific papers are most often cited by **Asta**, an agentic research platform that uses retrieval-augmented generation (RAG) to answer scientific questions. Each record corresponds to a citation event in Asta's *Summarize Literature* tool, showing which papers the system retrieved and cited across more than **113,000 user queries**, **four million citations** to over **two million distinct papers**.
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  By making these data public, we aim to create a transparent, trackable measure of which research most directly powers AI-generated answers—helping ensure that scientific contributions are visible and credited in the AI era.
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+ Weekly updates reflect ongoing usage patterns as Asta continues to evolve. We invite researchers, bibliometricians, and AI developers to explore citation dynamics across fields, assess how AI systems surface influential work, and help build a future where credit and accountability are integral to AI-assisted discovery.
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  The most recent update to the data can always be retrieved using the 'latest' config:
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  ## Dataset Details
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  - **Dataset name:** Asta Summary Citation Counts
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  - **Maintainer:** Allen Institute for AI (AI2)
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+ - **License and Use:** This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).
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  - **Update frequency:** Weekly
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  - **Source platform:** Asta (https://asta.ai)
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  - **Primary use cases:** bibliometrics, AI transparency, citation dynamics, evaluation of retrieval-augmented generation systems