anushakamath/test_c

Dataset Description:

The ChatRAG-Hi (Hindi ChatRAG Bench) dataset is based on the English version of the ChatRAG Bench, which comprises the following ten datasets: Doc2Dial, QuAC, QReCC, INSCIT, HybriDialogue, DoQA, and ConvFinQA. The dataset was translated using GCP, and approximately 500 samples were filtered from each of these sets based on backtranslation accuracy to eliminate poor translations.

Dataset Owner:

NVIDIA Corporation

Dataset Creation Date:

April 2025

License/Terms of Use:

This dataset is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

Intended Usage:

This dataset is used to evaluate a large language model’s (LLM) conversational QA capability over documents or retrieved context in the Hindi Language.

Dataset Characterization

Data Collection Method

• Synthetic
  

Labeling Method

• Synthetic
  

Dataset Format

Text

Dataset Quantification

474MB of prompt-response pairs, comprising 5948 individual samples.

Ethical Considerations:

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Citing

If you find our work helpful, please consider citing our paper:

@article{kamath2025benchmarking,
  title={Benchmarking Hindi LLMs: A New Suite of Datasets and a Comparative Analysis},
  author={Kamath, Anusha and Singla, Kanishk and Paul, Rakesh and Joshi, Raviraj and Vaidya, Utkarsh and Chauhan, Sanjay Singh and Wartikar, Niranjan},
  journal={arXiv preprint arXiv:2508.19831},
  year={2025}
}