RO-FIN-LLM: A Benchmark with LLM-as-a-Judge and Human Evaluators for Romanian Tax and Accounting

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Authors: Maria-Ecaterina Olariu, Vlad-Gabriel Buinceanu, Cristian Simionescu, Octavian Dospinescu, Răzvan Georgescu, Cezar Tudor, Adrian Iftene, Ana-Maria Bores
Cited by: 1
References: 16

Abstract

Large Language Models (LLMs) are increasingly being adopted in business settings; however, there remains a shortage of evaluation tools that account for country-specific regulations, particularly for Romania’s taxation and financial accounting requirements. RO-FIN-LLM is a benchmark designed to test how well LLMs handle Romania-specific regulatory question answering in taxation (including VAT regimes, income/profit tax, microenterprise rules, and other obligations) and financial accounting (including journal entries/monographs, amortization, provisions, and foreign exchange transactions). The benchmark contains questions curated by experts, each including the applicable regulatory time frames and the legal sources for the answers. Evaluation is performed in two protocols: closed-book and open-book with Retrieval Augmented Generation (RAG), using Tavily Search API. Evaluation metrics are represented by rubrics, namely correctness, legal citation quality, and clarity/structure. A subset of answers produced by three models was additionally evaluated by 12 specialists in the financial-accounting domain. In this revision, we also describe a public release plan for the question schema, prompts, and evaluation scripts to support independent reproducibility.

Fields of Study & Subjects

Artificial Intelligence in Law Legal Language and Interpretation Financial Reporting and XBRL

Publication details

Journal / source
Systems
Publisher
MDPI AG
Volume
14
Issue
3
Pages
244–244
Publication date
27 February 2026
Language
EN