Are LLM Assistants Regulatory Ready? Answers from regenold's 2026 EU AI Act Q&A Challenge

Large language model (LLM) assistants are increasingly proposed for regulatory affairs, yet their reliability in regulatory tasks remains unclear. We introduce the EU AI Act Q&A Benchmark, an expert-curated benchmark of 110 open-ended questions about the EU AI Act (Regulation (EU) 2024/1689). Each question comes with an exemplary answer, question-specific correctness criteria, and expected references. Evaluation measures answer correctness, reference quality, conciseness, tone, and latency, with a multi-turn ``hard mode'' testing responses to simulated user pushback. We also present the results of the 2026 EU AI Act Q&A Challenge, based on the benchmark, where three off-the-shelf baselines and five purpose-built assistants (from four commercial developers and one academic entrant) were tested. Only two of the five submitted assistants consistently outperformed the baselines; one achieved high scores across all evaluated metrics. These results show that specialist development alone does not guarantee better performance and highlight the critical importance of LLM assistant evaluation in regulatory affairs. The benchmark code is openly available at https://github.com/regenold-GmbH/eu-ai-act-benchmark-2026/.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-03
DOI
https://doi.org/10.48550/arxiv.2611.04546
Primary Topic
Artificial Intelligence in Law
Type
preprint
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preprint

Are LLM Assistants Regulatory Ready? Answers from regenold's 2026 EU AI Act Q&A Challenge

Marco Virgolin, Maximilian Regenold, Thomas Haszprunar
arXiv (Cornell University)
Artificial Intelligence in Law
preprint

Are LLM Assistants Regulatory Ready? Answers from regenold's 2026 EU AI Act Q&A Challenge

Marco Virgolin, Maximilian Regenold, Thomas Haszprunar
preprint en

Abstract

Large language model (LLM) assistants are increasingly proposed for regulatory affairs, yet their reliability in regulatory tasks remains unclear. We introduce the EU AI Act Q&A Benchmark, an expert-curated benchmark of 110 open-ended questions about the EU AI Act (Regulation (EU) 2024/1689). Each question comes with an exemplary answer, question-specific correctness criteria, and expected references. Evaluation measures answer correctness, reference quality, conciseness, tone, and latency, with a multi-turn ``hard mode'' testing responses to simulated user pushback. We also present the results of the 2026 EU AI Act Q&A Challenge, based on the benchmark, where three off-the-shelf baselines and five purpose-built assistants (from four commercial developers and one academic entrant) were tested. Only two of the five submitted assistants consistently outperformed the baselines; one achieved high scores across all evaluated metrics. These results show that specialist development alone does not guarantee better performance and highlight the critical importance of LLM assistant evaluation in regulatory affairs. The benchmark code is openly available at https://github.com/regenold-GmbH/eu-ai-act-benchmark-2026/.

arXiv (Cornell University)
Artificial Intelligence in Law
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Are LLM Assistants Regulatory Ready? Answers from regenold's 2026 EU AI Act Q&A Challenge — Marco Virgolin, Maximilian Regenold, et al. · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS