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BEAR-probe

Benchmark for Evaluating Associative Reasoning

홈페이지 · 논문 1편

The $\text{BEAR}$ dataset and its larger version, $\text{BEAR}_{\text{big}}$, 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}, } ``

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