Question Difficulty Estimation for Large Language Models via Answer Plausibility Scoring (2026.acl-long)
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| Challenge: | Existing approaches to estimate question difficulty rely on readability formulas, retrieval-based signals, or popularity statistics. |
| Approach: | They propose a method that estimates question difficulty by computing the entropy of plausibility scores over candidate answers. |
| Outcome: | The proposed method outperforms baselines across four QA datasets and shows strong robustness across hyperparameter variations and question types. |
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