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iit-patna-cse-ai/ArogyaBodha_ActCri

ArogyaBodha_ActCri Parallel (wide) variant for the actor-critic framework; each row pairs a local-language case with its English translation. Splits: train ~32,250 / test 3,500 (symmetric 500-cid holdout). Columns Column Type Description lid Value('string') Language-scoped id language Value('string') Case language Figure_A Image(mode=None, decode=True) Medical image Figure_B Image(mode=None, decode=True) Medical image Figure_C Image(mode=None… See the full description on the dataset page: https://huggingface.co/datasets/iit-patna-cse-ai/ArogyaBodha_ActCri.

sourceHugging Faceupdated 2mo agoView on Hugging Face
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ArogyaBodha_ActCri

Parallel (wide) variant for the actor-critic framework; each row pairs a local-language case with its English translation. Splits: train ~32,250 / test 3,500 (symmetric 500-cid holdout).

Columns

ColumnTypeDescription
lidValue('string')Language-scoped id
languageValue('string')Case language
Figure_AImage(mode=None, decode=True)Medical image
Figure_BImage(mode=None, decode=True)Medical image
Figure_CImage(mode=None, decode=True)Medical image
Figure_DImage(mode=None, decode=True)Medical image
Figure_EImage(mode=None, decode=True)Medical image
QuestionValue('string')Question text
Options{'A': Value('string'), 'B': Value('string'), 'C': Value('string'), 'D': Value('string'), 'E': Value('string')}Options A-E
Correct_answerValue('string')Correct key (A-E)
domain_systemValue('string')Body system / domain
difficulty_levelValue('int64')Difficulty (1-4)
sourceValue('string')Source dataset
Question_EngValue('string')English question
Options_Eng{'A': Value('string'), 'B': Value('string'), 'C': Value('string'), 'D': Value('string'), 'E': Value('string')}English options A-E

Citation

If you use this dataset in your research, please cite our paper:

Paper: ArogyaSutra (IJCAI 2026)

  • —arXiv: https://arxiv.org/abs/2606.13572
  • —Hugging Face: https://huggingface.co/papers/2606.13572
bibtex
    @inproceedings{halder2026arogyasutra,
      title     = {ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages},
      author    = {Halder, Tanmoy Kanti and Ghosh, Akash and Baidya, Subhadip and Roy, Arijit and Saha, Sriparna},
      booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI)},
      year      = {2026},
      url       = {https://github.com/IITP-CSE/ArogyaSutra}
      }