| # HEAD-QA | |
| ### Paper | |
| HEAD-QA: A Healthcare Dataset for Complex Reasoning | |
| https://arxiv.org/pdf/1906.04701.pdf | |
| HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the | |
| Spanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio | |
| de Sanidad, Consumo y Bienestar Social. | |
| The dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology. | |
| Homepage: https://aghie.github.io/head-qa/ | |
| ### Citation | |
| ``` | |
| @inproceedings{vilares-gomez-rodriguez-2019-head, | |
| title = "{HEAD}-{QA}: A Healthcare Dataset for Complex Reasoning", | |
| author = "Vilares, David and | |
| G{\'o}mez-Rodr{\'i}guez, Carlos", | |
| booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics", | |
| month = jul, | |
| year = "2019", | |
| address = "Florence, Italy", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://www.aclweb.org/anthology/P19-1092", | |
| doi = "10.18653/v1/P19-1092", | |
| pages = "960--966", | |
| abstract = "We present HEAD-QA, a multi-choice question answering testbed to encourage research on complex reasoning. The questions come from exams to access a specialized position in the Spanish healthcare system, and are challenging even for highly specialized humans. We then consider monolingual (Spanish) and cross-lingual (to English) experiments with information retrieval and neural techniques. We show that: (i) HEAD-QA challenges current methods, and (ii) the results lag well behind human performance, demonstrating its usefulness as a benchmark for future work.", | |
| } | |
| ``` | |
| ### Groups and Tasks | |
| #### Groups | |
| - `headqa`: Evaluates `headqa_en` and `headqa_es` | |
| #### Tasks | |
| * `headqa_en` - English variant of HEAD-QA | |
| * `headqa_es` - Spanish variant of HEAD-QA | |
| ### Checklist | |
| * [x] 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: | |
| * [x] Is the "Main" variant of this task clearly denoted? | |
| * [x] 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?\ | |
| * [x] Same as LM Evaluation Harness v0.3.0 implementation | |