Passing the Brazilian OAB Exam: data preparation and some experiments
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Abstract (arXiv)
In Brazil, all legal professionals must demonstrate their knowledge of the law and its application by passing the OAB exams, the national bar exams. The OAB exams therefore provide an excellent benchmark for the performance of legal information systems since passing the exam would arguably signal that the system has acquired capacity of legal reasoning comparable to that of a human lawyer. This article describes the construction of a new data set and some preliminary experiments on it, treating the problem of finding the justification for the answers to questions. The results provide a baseline performance measure against which to evaluate future improvements. We discuss the reasons to the poor performance and propose next steps.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Dec 2017.
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Citing papers per year: 2024: 2; 2025: 4.
6 papers.
- 2025Multilingual != Multicultural: Evaluating Gaps Between Multilingual Capabilities and Cultural Alignment in LLMscited by 39
- 2024Tucano: Advancing Neural Text Generation for Portuguesecited by 13
- 2024LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domaincited by 10
- 2025PoETa v2: Toward More Robust Evaluation of Large Language Models in Portuguesecited by 5
- 2025BLUEX Revisited: Enhancing Benchmark Coverage with Automatic Captioningcited by 3
- 2025BRoverbs -- Measuring how much LLMs understand Portuguese proverbscited by 3
- 2025PoETa v2: Toward More Robust Evaluation of Large Language Models in Portuguese21 Nov 2025
- 2025BRoverbs -- Measuring how much LLMs understand Portuguese proverbs10 Sep 2025
- 2025BLUEX Revisited: Enhancing Benchmark Coverage with Automatic Captioning29 Aug 2025
- 2025Multilingual != Multicultural: Evaluating Gaps Between Multilingual Capabilities and Cultural Alignment in LLMs23 Feb 2025
- 2024Tucano: Advancing Neural Text Generation for Portuguese12 Nov 2024
- 2024LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain2 Apr 2024