Hyeongdon Moon, Yoonseok Yang, Hangyeol Yu, Seunghyun Lee, Myeongho Jeong, Juneyoung Park, Jamin Shin, Minsam Kim, Seungtaek Choi
| Challenge: | Existing evaluation metrics for MCQ generation focus on the n-gram based similarity of the generated MCq to the gold sample and disregard their educational value. |
| Approach: | They propose to use a human survey to measure the MCQ’s answerability given knowledge of the target fact. |
| Outcome: | The proposed methods measure the MCQ’s answerability given knowledge of the target fact. |
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| Challenge: | Existing evaluation metrics based on n-gram similarity do not correlate well with human judgments . large datasets for document Question Answering (QA) have enabled the development of end-to-end supervised models . |
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Revisiting the Self-Consistency Challenges in Multi-Choice Question Formats for Large Language Model Evaluation (2024.lrec-main)
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| Challenge: | Multi-choice questions (MCQs) are a common method for assessing the world knowledge of large language models. |
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Sérgio Silva Mucciaccia, Thiago Meireles Paixão, Filipe Wall Mutz, Claudine Santos Badue, Alberto Ferreira de Souza, Thiago Oliveira-Santos
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Evaluating Question Answering Evaluation (D19-58)
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| Challenge: | Existing n-gram based QA metrics have a number of drawbacks and are not suitable for all extractive tasks. |
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| Challenge: | Multiple choice question answering (MCQA) is popular for LLM evaluation due to its simplicity and human-like testing. |
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Can Multiple-choice Questions Really Be Useful in Detecting the Abilities of LLMs? (2024.lrec-main)
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Wanyong Feng, Jaewook Lee, Hunter McNichols, Alexander Scarlatos, Digory Smith, Simon Woodhead, Nancy Ornelas, Andrew Lan
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MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedback (2025.naacl-long)
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| Challenge: | Generating multiple-choice questions (MCQG) for professional exams is challenging due to outdated knowledge, hallucination issues, and prompt sensitivity. |
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Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction (2025.acl-long)
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| Challenge: | Multiple-choice questions (MCQs) are critical for identifying misconceptions and gaps in knowledge and accurately assessing students' understanding. |
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