| # LogiQA | |
| ### Paper | |
| Title: `LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning` | |
| Abstract: https://arxiv.org/abs/2007.08124 | |
| LogiQA is a dataset for testing human logical reasoning. It consists of 8,678 QA | |
| instances, covering multiple types of deductive reasoning. Results show that state- | |
| of-the-art neural models perform by far worse than human ceiling. The dataset can | |
| also serve as a benchmark for reinvestigating logical AI under the deep learning | |
| NLP setting. | |
| Homepage: https://github.com/lgw863/LogiQA-dataset | |
| ### Citation | |
| ``` | |
| @misc{liu2020logiqa, | |
| title={LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning}, | |
| author={Jian Liu and Leyang Cui and Hanmeng Liu and Dandan Huang and Yile Wang and Yue Zhang}, | |
| year={2020}, | |
| eprint={2007.08124}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| ``` | |
| ### Groups and Tasks | |
| #### Groups | |
| * Not part of a group yet | |
| #### Tasks | |
| * `logiqa` | |
| ### Checklist | |
| For adding novel benchmarks/datasets to the library: | |
| * [ ] Is the task an existing benchmark in the literature? | |
| * [ ] Have you referenced the original paper that introduced the task? | |
| * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? | |
| If other tasks on this dataset are already supported: | |
| * [ ] Is the "Main" variant of this task clearly denoted? | |
| * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? | |
| * [ ] Have you noted which, if any, published evaluation setups are matched by this variant? | |