Datasets › FaVIQ
FaVIQ (Fact Verification from Information-seeking Questions)
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.
Source: https://faviq.github.io
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 15 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- FaVIQ
1 variant name, as the archive lists them.
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