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--- |
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language: |
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- fr |
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- es |
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- zh |
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size_categories: |
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- 1K<n<10K |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: "test/data-00000-of-00001.arrow" |
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--- |
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# MultiNRC: Multilingual Native Reasoning Challenge |
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MultiNRC is a challenging evaluation benchmark for large language models, designed to assess multilingual reasoning ability in French, Spanish, and Chinese. Unlike existing benchmarks that simply translate English-centric content, MultiNRC consists of over 1,000 native-authored reasoning questions, crafted by native speakers to capture linguistic and cultural nuances. |
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## Features |
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- **Languages:** French, Spanish, Chinese |
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- **Categories:** |
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- Language-specific Linguistic Reasoning |
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- Wordplay & Riddles |
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- Cultural Reasoning & Traditions |
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- Math Reasoning with Cultural Relevance |
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- **English Equivalents:** For Cultural/Tradition and Math, human-translated English versions are provided for direct comparison. |
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- **Ground Truth Final Answers:** Short, objective answers accompany each prompt for automatic evaluation. |
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## Dataset Structure |
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Each entry includes: |
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- A native-language prompt and answer (`i18n_prompt`, `i18n_gtfa`) |
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- (For Math Reasoning and Cultural Reasoning category tasks) An English-equivalent prompt and answer (`english_prompt`, `english_gtfa`) |
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- Metadata: `task_id`, `language`, `category` |
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## Citation |
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If you use MultiNRC in your research, please cite: |
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```bibtex |
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@article{fabbri2025multinrc, |
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title = {MultiNRC: A Challenging Native Multilingual Reasoning Evaluation Benchmark for LLMs}, |
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author = {Fabbri, Alexander R. and Mares, Diego and Flores, Jorge and Mankikar, Meher and Hernandez, Ernesto and Lee, Dean and Liu, Bing and Xing, Chen}, |
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year = {2025}, |
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note = {arXiv preprint, arXiv:XXXX.XXXXX} |
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} |
