What Makes Something Hard(er)? Explaining Question Difficulty in Natural Language
Difficulty is one of the most fundamental properties of a question: it determines whether the question can meaningfully discriminate between models of differing ability. Although a variety of methods can now estimate or predict difficulty automatically, they yield only a single descriptive number, with no account of the underlying factors that make a question difficult in the first place. In this work, we propose a data-driven approach that automatically generates and validates natural-language hypotheses explaining what makes one question harder than another. We first estimate each item's difficulty from the responses of a large pool of LLMs using Item Response Theory. We then sample con...
| Authors | Peng Cui, Qiaoyuan Zheng, Rudolf Debelak et al. |
|---|---|
| Primary category | cs.CL |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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