Datasets › FanOutQA
FanOutQA
FanOutQA is a high quality, multi-hop, multi-document benchmark for large language models using English Wikipedia as its knowledge base. Compared to other question-answering benchmarks, FanOutQA requires reasoning over a greater number of documents, with the benchmark's main focus being on the titular fan-out style of question. We present these questions in three tasks -- closed-book, open-book, and evidence-provided -- which measure different abilities of LLM systems.
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 3 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
Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- FanOutQA
1 variant name, as the archive lists them.
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