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.
CITATION STYLE
Vilares, D., & Gómez-Rodríguez, C. (2020). HEAD-QA: A healthcare dataset for complex reasoning. In ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (pp. 960–966). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p19-1092
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