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Dataset: reclor 🏷
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How to load this dataset directly with the πŸ€—/datasets library:

				
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from datasets import load_dataset dataset = load_dataset("reclor")

Description

Logical reasoning is an important ability to examine, analyze, and critically evaluate arguments as they occur in ordinary language as the definition from LSAC. ReClor is a dataset extracted from logical reasoning questions of standardized graduate admission examinations. Empirical results show that the state-of-the-art models struggle on ReClor with poor performance indicating more research is needed to essentially enhance the logical reasoning ability of current models. We hope this dataset could help push Machine Reading Comprehension (MRC) towards more complicated reasonin

Citation

@inproceedings{yu2020reclor,
        author = {Yu, Weihao and Jiang, Zihang and Dong, Yanfei and Feng, Jiashi},
        title = {ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning},
        booktitle = {International Conference on Learning Representations (ICLR)},
        month = {April},
        year = {2020}
    }

Models trained or fine-tuned on reclor

None yet. Start fine-tuning now =)