{"url":"/dataset/faviq","name":"FaVIQ","full_name":"Fact Verification from Information-seeking Questions","description_markdown":"**FaVIQ** (Fact Verification from Information-seeking Questions) is a challenging and realistic fact verification dataset that reflects confusions raised by real users. We use the ambiguity in information-seeking questions and their disambiguation, and automatically convert them to true and false claims. These claims are natural, and require a complete understanding of the evidence for verification. FaVIQ serves as a challenging benchmark for natural language understanding, and improves performance in professional fact checking.\r\n\r\nSource: [https://faviq.github.io](https://faviq.github.io)","description_withheld":null,"homepage":"https://faviq.github.io","introduced_date":"2021-07-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/faviq-fact-verification-from-information","title":"FaVIQ: FAct Verification from Information-seeking Questions","first_author":"Jungsoo Park","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Fact Verification","url":"/task/fact-verification","datasets_with_task":"/datasets/task/fact-verification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["FaVIQ"],"data_loaders":[],"num_papers_in_archive":15,"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."}