Datasets › SummEdits
SummEdits
SummEdits is a benchmark designed to measure the ability of Large Language Models (LLMs) to reason about facts and detect inconsistencies. It was proposed as a new protocol for inconsistency detection benchmark creation.
The SummEdits benchmark is implemented across 10 domains. It is 20 times more cost-effective per sample than previous benchmarks and highly reproducible, with an estimated inter-annotator agreement of about 0.91.
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 5 papers for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- SummEdits
1 variant name, as the archive lists them.
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