| --- |
| language: |
| - fr |
| - es |
| - zh |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: "test/data-00000-of-00001.arrow" |
| --- |
| |
| # MultiNRC: Multilingual Native Reasoning Challenge |
|
|
| 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. |
|
|
| ## Features |
|
|
| - **Languages:** French, Spanish, Chinese |
| - **Categories:** |
| - Language-specific Linguistic Reasoning |
| - Wordplay & Riddles |
| - Cultural Reasoning & Traditions |
| - Math Reasoning with Cultural Relevance |
| - **English Equivalents:** For Cultural/Tradition and Math, human-translated English versions are provided for direct comparison. |
| - **Ground Truth Final Answers:** Short, objective answers accompany each prompt for automatic evaluation. |
|
|
|
|
| ## Dataset Structure |
|
|
| Each entry includes: |
| - A native-language prompt and answer (`i18n_prompt`, `i18n_gtfa`) |
| - (For Math Reasoning and Cultural Reasoning category tasks) An English-equivalent prompt and answer (`english_prompt`, `english_gtfa`) |
| - Metadata: `task_id`, `language`, `category` |
|
|
| ## Citation |
|
|
| If you use MultiNRC in your research, please cite: |
|
|
| ```bibtex |
| @article{fabbri2025multinrc, |
| title = {MultiNRC: A Challenging Native Multilingual Reasoning Evaluation Benchmark for LLMs}, |
| 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}, |
| year = {2025}, |
| note = {arXiv preprint, arXiv:XXXX.XXXXX} |
| } |
