{"url":"/dataset/orconvqa","name":"ORConvQA","full_name":"Open-Retrieval Conversational Question Answering","description_markdown":"Enhances QuAC by adapting it to an open-retrieval setting. It is an aggregation of three existing datasets: (1) the QuAC dataset that offers information-seeking conversations, (2) the CANARD dataset that consists of context-independent rewrites of QuAC questions, and (3) the Wikipedia corpus that serves as the knowledge source of answering questions.\r\n\r\nSource: [ORConvQA](https://github.com/prdwb/orconvqa-release)","description_withheld":null,"homepage":"https://github.com/prdwb/orconvqa-release","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/open-retrieval-conversational-question","title":"Open-Retrieval Conversational Question Answering","first_author":"Chen Qu","url":null},"license":null,"modalities":[],"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"}],"languages":[],"variants":["ORConvQA"],"data_loaders":[{"repo":"https://github.com/prdwb/orconvqa-release","url":"https://github.com/prdwb/orconvqa-release","frameworks":["pytorch"]}],"num_papers_in_archive":17,"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."}