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# EusTrivia |
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### Paper |
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Title: Latxa: An Open Language Model and Evaluation Suite for Basque |
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Abstract: https://arxiv.org/abs/2403.20266 |
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EusTrivia consists of 1,715 trivia questions from multiple online sources. 56.3\% of the questions are elementary level (grades 3-6), while the rest are considered challenging. A significant portion of the questions focus specifically on the Basque Country, its language and culture. Each multiple-choice question contains two, three or four choices (3.84 on average) and a single correct answer. Five areas of knowledge are covered: |
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- **Humanities and Natural Sciences** (27.8%): This category encompasses questions about history, geography, biology, ecology and other social and natural sciences. |
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- **Leisure and Art** (24.5%): This category includes questions on sports and athletes, performative and plastic arts and artists, architecture, cultural events, and related topics. |
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- **Music** (16.0%): Here are grouped all the questions about music and musicians, both classical and contemporary. |
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- **Language and Literature** (17.1%): This category is concerned with all kinds of literature productions and writers, as well as metalinguistic questions (e.g., definitions, synonyms, and word usage). |
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- **Mathematics and ICT** (14.5%): This category covers mathematical problems and questions about ICT, as well as questions about people known for their contributions to these fields of knowledge. |
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Homepage: https://github.com/hitz-zentroa/latxa |
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### Citation |
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``` |
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@misc{etxaniz2024latxa, |
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title={Latxa: An Open Language Model and Evaluation Suite for Basque}, |
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author={Julen Etxaniz and Oscar Sainz and Naiara Perez and Itziar Aldabe and German Rigau and Eneko Agirre and Aitor Ormazabal and Mikel Artetxe and Aitor Soroa}, |
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year={2024}, |
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eprint={2403.20266}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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### Groups and Tasks |
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#### Groups |
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There are no groups. |
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#### Tasks |
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* `eus_trivia`: EusTrivia consists of 1,715 trivia questions from multiple online sources. |
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### Checklist |
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For adding novel benchmarks/datasets to the library: |
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* [ ] Is the task an existing benchmark in the literature? |
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* [ ] Have you referenced the original paper that introduced the task? |
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* [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? |
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If other tasks on this dataset are already supported: |
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* [ ] Is the "Main" variant of this task clearly denoted? |
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* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? |
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* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? |
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