Datasets › BEAR-probe

BEAR-probe (Benchmark for Evaluating Associative Reasoning)

Introduced by Jacek Wiland et al. in BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models5 Apr 2024 archive 2025-07-28

The BEAR dataset and its larger version, BEAR_(big), are benchmarks for evaluating common factual knowledge contained in language models.

This dataset was created as part of the paper "BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models".

For more information visit the LM Pub Quiz website.

Citation

When using the dataset or library, please cite the following paper:

@misc{wilandBEARUnifiedFramework2024,
  title = {{{BEAR}}: {{A Unified Framework}} for {{Evaluating Relational Knowledge}} in {{Causal}} and {{Masked Language Models}}},
  shorttitle = {{{BEAR}}},
  author = {Wiland, Jacek and Ploner, Max and Akbik, Alan},
  year = {2024},
  number = {arXiv:2404.04113},
  eprint = {2404.04113},
  publisher = {arXiv},
  url = {http://arxiv.org/abs/2404.04113},
}

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

License archive 2025-07-28

CC BY-SA

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • BEAR-probe

1 variant name, as the archive lists them.

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