Datasets › Olympic 2024

Olympic 2024

Introduced by Qiujie Xie et al. in An Empirical Analysis of Uncertainty in Large Language Model Evaluations15 Feb 2025 archive 2025-07-28

Olympic 2024 is a human-annotated dataset that contains 220 high-quality instance. Each instance consists of an input tuple (user instruction, response 1, response confidence of response 1, response 2, response confidence of response 2) and an output tuple (evaluation explanation, evaluation result). The evaluation result would be either ‘1’ or ‘2’, indicating that response 1 or response 2 is better. To ensure the quality of human annotations, we involve three experts to concurrently annotate the same data point during the annotation process.

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

Creative Commons Attribution Non Commercial Share Alike 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • Olympic 2024

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