{"url":"/dataset/reqa","name":"ReQA","full_name":"Retrieval Question-Answering","description_markdown":"Retrieval Question-Answering (ReQA) benchmark tests a model’s ability to retrieve relevant answers efficiently from a large set of documents.\r\n\r\nSource: [ReQA: An Evaluation for End-to-End Answer Retrieval Models](https://arxiv.org/pdf/1907.04780.pdf)","description_withheld":null,"homepage":"https://github.com/google/retrieval-qa-eval","introduced_date":"2019-07-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/reqa-an-evaluation-for-end-to-end-answer","title":"ReQA: An Evaluation for End-to-End Answer Retrieval Models","first_author":"Amin Ahmad","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Information Retrieval","url":"/task/information-retrieval","datasets_with_task":"/datasets/task/information-retrieval"},{"name":"Learning-To-Rank","url":"/task/learning-to-rank","datasets_with_task":"/datasets/task/learning-to-rank"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ReQA"],"data_loaders":[{"repo":"https://github.com/google/retrieval-qa-eval","url":"https://github.com/google/retrieval-qa-eval","frameworks":["tf"]}],"num_papers_in_archive":10,"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."}