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October 20, 2025Open Access

MinosEval: Distinguishing Factoid and Non-Factoid for Tailored Open-Ended QA Evaluation with LLMs

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MinosEval improves evaluation by clearly distinguishing factoid and non-factoid questions.
It employs adaptive scoring for factoid questions and instance-aware ranking for non-factoid questions.
Experiments confirm that MinosEval aligns better with human judgments compared to traditional metrics.
This method addresses the shortcomings of existing LLM-based evaluation approaches in automatic assessment.

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MinosEval distinguishes between factoid and non-factoid questions, enhancing evaluation accuracy in LLMs.

Fan et al. (2025) studied this question.

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