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allenai/asta-summary-citation-counts

Dataset Summary 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 is a paper cited by Asta's Summarize Literature tool, ranked by the number of times the system cited that paper. Across more than 113,000 user queries, we track 4M citations to over 2M distinct papers. By making this data public, we aim to create a transparent, trackable… See the full description on the dataset page: https://huggingface.co/datasets/allenai/asta-summary-citation-counts.

sourceHugging Faceodc-byupdated 3d agoView on Hugging Face
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Dataset Summary

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 is a paper cited by Asta's Summarize Literature tool, ranked by the number of times the system cited that paper. Across more than 113,000 user queries, we track 4M citations to over 2M distinct papers. By making this 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.

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.

The most recent update to the data can always be retrieved using the 'latest' config:

dataset = load_dataset("allenai/asta-summary-citation-counts", "latest")

Older checkpoints can be retrieved by date. Eg:

dataset = load_dataset("allenai/asta-summary-citation-counts", "2025-10-07")

Column Descriptions

**Field Name****Description**
corpus_idUnique identifier for the paper from Semantic Scholar
titleTitle of the paper
sqa_citation_rankOverall rank of the paper in terms of unique citation counts across queries on Asta Literature Summarizer
sqa_citation_count_queriesUnique citation counts of the paper across queries that powers its sqa_citation_rank
sqa_citation_count_total_citationsTotal citation counts of the paper across queries (A paper can be cited multiple times in the answer report to a query)
authorsComma separated string of paper authors
venuePublishing venue/conference/journal of the paper
yearYear of publishing of the paper
s2FieldsOfStudyAcademic field of study categories assigned to the paper in Semantic Scholar by their classifier. The possible fields are: Computer Science, Medicine, Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art, History, Geography, Sociology, Business, Political Science, Economics, Philosophy, Mathematics, Engineering, Environmental Science, Agricultural and Food Sciences, Education, Law, and Linguistics.

Dataset Details

  • —Dataset name: Asta Summary Citation Counts
  • —Maintainer: Allen Institute for AI (AI2)
  • —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.
  • —Update frequency: Weekly
  • —Source platform: Asta (https://asta.ai)
  • —System Paper: Ai2 Scholar QA: Organized Literature Synthesis with Attribution
  • —System Code: ai2-scholarqa-lib
  • —Primary use cases: bibliometrics, AI transparency, citation dynamics, evaluation of retrieval-augmented generation systems