None of the Above, Less of the Right Parallel Patterns in Human and LLM Performance on Multi-Choice Questions Answering

Multiple-choice exam questions with "None of the above" (NA) options have been extensively studied in educational testing, in which existing research suggests that they better assess true knowledge.However, their impact on Large Language Models (LLMs) evaluation remains underexplored.Through systematic experiments with 28 LLMs on the MMLU benchmark, we examine how NA options affect model performance and confidence calibration.Our analysis reveals that NA options, when used as the correct answer, lead to a consistent 30-50% performance drop across models regardless of scale-suggesting that LLMs lack the meta-cognitive ability to systematically evaluate and reject all given options when none are correct.This degradation shows strong domain dependence, with minimal impact on mathematical reasoning (14.6% drop) but severe effects on tasks requiring uncertainty handling like business ethics (48.1% drop).Our results highlight important implications for benchmark design and raise questions about LLMs' ability to handle uncertainty in realworld applications. * Equal contributionStandard choice Answer absent choice Question: Which of the following are steroid-based molecules?I. Testosterone ( ) II.Triglycerides () III.Progesterone ( ) IV.DNA () A. I only B. I, II, and III C. I and III D. I, III, and IV A. I only B. I, II, and III C. I, III, and IV

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.1031
Citations
1
Primary Topic
Expert finding and Q&A systems
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article
Field-Weighted Citation Impact
3.25
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article

None of the Above, Less of the Right Parallel Patterns in Human and LLM Performance on Multi-Choice Questions Answering

Chieh-Yen Lin, Zhi Rui Tam, Chunfei Wu, Yun-Nung Chen
1 citations
Expert finding and Q&A systems
3.25
article

None of the Above, Less of the Right Parallel Patterns in Human and LLM Performance on Multi-Choice Questions Answering

Chieh-Yen Lin, Zhi Rui Tam, Chunfei Wu, Yun-Nung Chen
article en
1 citations

Abstract

Multiple-choice exam questions with "None of the above" (NA) options have been extensively studied in educational testing, in which existing research suggests that they better assess true knowledge.However, their impact on Large Language Models (LLMs) evaluation remains underexplored.Through systematic experiments with 28 LLMs on the MMLU benchmark, we examine how NA options affect model performance and confidence calibration.Our analysis reveals that NA options, when used as the correct answer, lead to a consistent 30-50% performance drop across models regardless of scale-suggesting that LLMs lack the meta-cognitive ability to systematically evaluate and reject all given options when none are correct.This degradation shows strong domain dependence, with minimal impact on mathematical reasoning (14.6% drop) but severe effects on tasks requiring uncertainty handling like business ethics (48.1% drop).Our results highlight important implications for benchmark design and raise questions about LLMs' ability to handle uncertainty in realworld applications. * Equal contributionStandard choice Answer absent choice Question: Which of the following are steroid-based molecules?I. Testosterone ( ) II.Triglycerides () III.Progesterone ( ) IV.DNA () A. I only B. I, II, and III C. I and III D. I, III, and IV A. I only B. I, II, and III C. I, III, and IV

Openalex Percentile: Top 7%
Expert finding and Q&A systems
3.25
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None of the Above, Less of the Right Parallel Patterns in Human and LLM Performance on Multi-Choice Questions Answering — Chieh-Yen Lin, Zhi Rui Tam, et al. · (2025) | TGRS Research Map | TGRS