mlsanityData to 13 Oct 2026

HEAD-QA: A Healthcare Dataset for Complex Reasoning

arXiv 1906.04701 ↗First posted 11 Jun 2019cs.CLcited by 101

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Abstract (arXiv)

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.

Key facts. Cited by 101 papers in the map (data through 13 Oct 2026). First posted on arXiv 11 Jun 2019.

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Citing papers per year: 2021: 6; 2022: 9; 2023: 15; 2024: 20; 2025: 29; 2026: 22.

101 papers.

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  11. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
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38 more
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  6. 2021Biomedical Question Answering: A Survey of Approaches and Challengescited by 46
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  9. 2024Towards Evaluating and Building Versatile Large Language Models for Medicinecited by 39
  10. 2024Apollo: A Lightweight Multilingual Medical LLM towards Democratizing Medical AI to 6B Peoplecited by 38
  11. 2025MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworkscited by 38
  12. 2021Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Reviewcited by 35
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  17. 2023FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical domaincited by 25
  18. 2025MedS3: Towards Medical Slow Thinking with Self-Evolved Soft Dual-sided Process Supervisioncited by 24
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  21. 2024Data Contamination Report from the 2024 CONDA Shared Taskcited by 20
  22. 2022RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Questioncited by 17
  23. 2024Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Expertscited by 17
  24. 2025Disentangling Reasoning and Knowledge in Medical Large Language Modelscited by 17
  25. 2021Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Managementcited by 16
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  31. 2022Active Few-Shot Learning with FASLcited by 11
  32. 2023Enhancing Small Medical Learners with Privacy-preserving Contextual Promptingcited by 11
  33. 2024CasiMedicos-Arg: A Medical Question Answering Dataset Annotated with Explanatory Argumentative Structurescited by 11
  34. 2024WorldMedQA-V: a multilingual, multimodal medical examination dataset for multimodal language models evaluationcited by 11
  35. 2025BioMaze: Benchmarking and Enhancing Large Language Models for Biological Pathway Reasoningcited by 10
  36. 2025OctoMed: Data Recipes for State-of-the-Art Multimodal Medical Reasoningcited by 10
  37. 2024Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMscited by 8
  38. 2026Conformal Selective Acting: Anytime-Valid Risk Control for RLVR-Trained LLMscited by 8

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