Datasets › PubMedAbstractsSubsetEmbedded

PubMedAbstractsSubsetEmbedded

Introduced by Linus Stuhlmann et al. in Efficient and Reproducible Biomedical Question Answering using Retrieval Augmented Generation19 Mar 2025 archive 2025-07-28

This dataset contains a probabilistic sample of ~2.4 million PubMed abstracts, enriched with precomputed dense embeddings (title + abstract), from the ncbi/MedCPT-Article-Encoder model. It is derived from public metadata made available via the National Library of Medicine (NLM) and was used in the paper Efficient and Reproducible Biomedical QA using Retrieval-Augmented Generation.

Each entry includes: - title: Title of the publication - abstract: Abstract content - PMID: PubMed identifier - embedding: 768-dimensional float32 vector from MedCPT

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

CC-BY-4.0

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

Variants archive 2025-07-28

  • PubMedAbstractsSubsetEmbedded

1 variant name, as the archive lists them.

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