Datasets › Off-Topic
Off-Topic
This dataset consists of synthetic LLM system prompts paired with user prompts, classified as either off-topic or on-topic. The aim is to provide realistic, real-world-inspired examples reflecting how large language models (LLMs) are used today for both open-ended and closed-ended tasks, such as text generation and classification. This dataset can be used for training and benchmarking off-topic guardrails.
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 1 paper 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
- Off-Topic
1 variant name, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections