{"url":"/dataset/pqaref","name":"PQAref","full_name":"Pubmed Question Answering with references","description_markdown":"The PQAref dataset is a dataset for fine-tuning large language models for referenced question-answering in biomedical domain.\r\n\r\nThe dataset contains 3 components:\r\n\r\nInstruction - question that is supposed to be answered\r\nAbstracts - set of 10 relevant abstracts retrieved from PubMed by an IR system. They contain the PubMed id, abstract title and the content of the abstract\r\nAnswer - expected answer, with references in the form of PubMed IDs.\r\n\r\nThe dataset was created semi-automatically, utilizing questions available from PubMedQA dataset.\r\n\r\nThe dataset contains 9,075 samples, split into training, validation and test set in proportion 80%:10%:10%.","description_withheld":null,"homepage":"https://huggingface.co/datasets/BojanaBas/PQAref","introduced_date":"2024-07-06","introduced_date_note":null,"introduced_by":{"paper":"/paper/how-do-you-know-that-teaching-generative","title":"How do you know that? Teaching Generative Language Models to Reference Answers to Biomedical Questions","first_author":"Bojana Bašaragin","url":null},"license":{"name":"AGPLv3","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["PQAref"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}