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arXiv · 2508.16838

If We May De-Presuppose: Robustly Verifying Claims through Presupposition-Free Question Decomposition

Shubhashis Roy Dipta·Francis Ferraro
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Abstract

Prior work has shown that presupposition in generated questions can introduce unverified assumptions, leading to inconsistencies in claim verification. Additionally, prompt sensitivity remains a significant challenge for large language models (LLMs), resulting in performance variance as high as 3-6%. While recent advancements have reduced this gap, our study demonstrates that prompt sensitivity remains a persistent issue. To address this, we propose a structured and robust claim verification framework that reasons through presupposition-free, decomposed questions. Extensive experiments across multiple prompts, datasets, and LLMs reveal that even state-of-the-art models remain susceptible to prompt variance and presupposition. Our method consistently mitigates these issues, achieving up to a 2-5% improvement.

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Shubhashis Roy Dipta, Francis Ferraro. 2025-08-22. If We May De-Presuppose: Robustly Verifying Claims through Presupposition-Free Question Decomposition. https://arxiv.org/abs/2508.16838

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