Metric assessment protocol in the context of answer fluctuation on MCQ tasks
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Abstract (arXiv)
Using multiple-choice questions (MCQs) has become a standard for assessing LLM capabilities efficiently. A variety of metrics can be employed for this task. However, previous research has not conducted a thorough assessment of them. At the same time, MCQ evaluation suffers from answer fluctuation: models produce different results given slight changes in prompts. We suggest a metric assessment protocol in which evaluation methodologies are analyzed through their connection with fluctuation rates, as well as original performance. Our results show that there is a strong link between existing metrics and the answer changing, even when computed without any additional prompt variants. A novel metric, worst accuracy, demonstrates the highest association on the protocol.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 28 of its 52 references that are in the map. First posted on arXiv 21 Jul 2025.
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References · 28
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16 more
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