datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
medmcqa
Dataset Card for MedMCQA
Dataset Summary
MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions.
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.
Each sample contains a question, correct answer(s), and other options which require… See the full description on the dataset page: https://huggingface.co/datasets/openlifescienceai/medmcqa.med_mcqaFrom "MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering"
(Pal et al.), MedMCQA is a "multiple-choice question answering (MCQA) dataset designed to address
real-world medical entrance exam questions." The dataset "...has more than 194k high-quality AIIMS & NEET PG
entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average
token length of 12.77 and high topical diversity."
The following is an example from… See the full description on the dataset page: https://huggingface.co/datasets/lighteval/med_mcqa.medical-logits-phi3.5-mini_medmcqa_pubmMedMCQA-Mixtral-CoT
Dataset Card for medmcqa-cot
Synthetically enhanced responses to the medmcqa dataset using mixtral.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedMCQA dataset, we leverage Mixtral-8x7B to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a
hand-crafted list of few-shot examples. For a multichoice answer, we ask the model to rephrase and explain the… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MedMCQA-Mixtral-CoT.medmcqa-gen-by-zephyr-ft-gpqa-allMedMCQA
MedMCQA - Medical Multiple Choice Question Answering
Description
This dataset contains multiple choice questions from Indian medical entrance exams (AIIMS/NEET). Questions cover various medical subjects with detailed explanations. 16 reasoning traces were collected for each example in this task by sampling with DeepSeek-R1, available in the responses column. We greatly appreciate and build from the original data source available at… See the full description on the dataset page: https://huggingface.co/datasets/OctoMed/MedMCQA.MedMCQA-Indicmedmcqa_generic_to_brandmedmcqa-gen-by-zephyr-ft-gpqa-all-sorted-contrastive-with-choices-subsampled_trakmedmcqa-gen-by-zephyr-ft-gpqa-all-sorted-contrastivemedmcqa-gen-by-zephyr-ft-gpqa-all-sorted-trakmedmcqa-gen-by-zephyr-ft-gpqa-all-sorted-contrastive-with-choicesc_medmcqa_it_Qwen3-32Bmedmcqa-cot-llama31
medqa-cot-llama31
Synthetically enhanced responses to the MedMCQA dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedMCQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medmcqa-cot-llama31.medmcqa-MedGENIE
Dataset Card for "medmcqa-MedGENIE"
Dataset Description
The data is a part of the MedGENIE collection of medical datasets augmented with artificial contexts generated by PMC-LLaMA-13B. Specifically, up to 5 artificial contexts were generated for each question in MedMCQA, employing a multi-view approach to encompass various perspectives associated with the given question.
The dataset has been used to train MedGENIE-fid-flan-t5-base-medmcqa allowing it to achieve… See the full description on the dataset page: https://huggingface.co/datasets/disi-unibo-nlp/medmcqa-MedGENIE.medmcqa-openai-native
MedMCQA — OpenAI-native, with a usable test split
MedMCQA is one of the most downloaded medical QA datasets on the Hub. Its test split has been unusable since release: all 6,150 rows carry cop=-1 (no label) and an empty explanation. You cannot score a model on it.
This release rebuilds a labelled, leak-free test split and converts everything to the native messages format, so it loads straight into TRL with no custom parsing.
What was actually wrong
Measured on the… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/medmcqa-openai-native.medmcqa_alpaca_format
Dataset Card for "medmcqa_alpaca_format"
More Information needed
sys_medmcqa_trainmedmcqa
MedMCQA (AIIMS & NEET PG Medical Entrance MCQs)
Dataset Summary
This dataset is a re-upload of the MedMCQA dataset introduced by Pal et al. in MedMCQA: A Large-Scale Multi-Subject Multi-Choice Dataset for Medical Domain Question Answering (ACL 2022).
MedMCQA is a large-scale multiple-choice question answering dataset sourced from Indian medical entrance examinations (AIIMS PG and NEET PG). It covers 20 medical subjects and contains over 194,000 questions with four answer… See the full description on the dataset page: https://huggingface.co/datasets/awinml/medmcqa.medmcqa_train_translated_es_with_chunks_es_kb_None_7000_dense_with_options_reformatted_contextmedmcqa_originalmedmcqa-ita-filteredsys_medmcqa_testmedmcqa_formattedbenchbase-medmcqaBenchBase: MedMCQA
193,000+ multiple-choice medical questions from Indian postgraduate medical entrance exams, spanning 2,400 healthcare topics.
Overview
BenchBase: MedMCQA is a repackaging of the MedMCQA dataset for the Layered Labs BenchBase
benchmark suite. The source dataset contains 193,155 multiple-choice questions drawn from
AIIMS and PGMR medical entrance examinations, covering 2,400+ healthcare topics across
clinical medicine… See the full description on the dataset page: https://huggingface.co/datasets/Layered-Labs/benchbase-medmcqa.medmcqa
Dataset Card for "medmcqa"
More Information needed
MedMCQA
MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering
Dataset Description
Links
Homepage:
Github.io
Repository:
Github
Paper:
arXiv
Leaderboard:
Papers with Code
Contact (Original Authors):
Aaditya Ura aadityaura@gmail.com), Logesh logesh.umapathi@saama.com
Contact (Curator):
Artur Guimarães (artur.guimas@gmail.com)
Dataset Summary
`MedMCQA has more than 194k high-quality AIIMS &… See the full description on the dataset page: https://huggingface.co/datasets/araag2/MedMCQA.medmcqa-itThis dataset is presented in
@misc{ferrazzi2025groundedmultilingualmedicalreasoning,
title={Grounded Multilingual Medical Reasoning for Question Answering with Large Language Models},
author={Pietro Ferrazzi and Aitor Soroa and Rodrigo Agerri},
year={2025},
eprint={2512.05658},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2512.05658},
}
Medprompt-MedMCQA-ToT
Medprompt-MedMCQA-ToT
Dataset Summary
Medprompt-MedMCQA-ToT is a retrieval-augmented database designed to enhance contextual reasoning in multiple-choice medical question answering (MCQA). The dataset follows a Tree-of-Thoughts (ToT) reasoning format, where multiple independent reasoning paths are explored collaboratively before arriving at the correct answer. This structured… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/Medprompt-MedMCQA-ToT.MedMCQA.20.01_terminate_aug