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Asking Again and Again: Exploring LLM Robustness to Repeated Questions

Repeating questions in prompts does not significantly improve the accuracy of large language models across various datasets and settings.

Year
2024
Venue
arXiv 2024
Authors
1
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arxiv.org/abs/2412.07923ARXIV-DEFAULT
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Abstract

This study examines whether large language models (LLMs), such as ChatGPT, specifically the latest GPT-4o-mini, exhibit sensitivity to repeated prompts and whether repeating a question can improve response accuracy. We hypothesize that reiterating a question within a single prompt might enhance the model's focus on key elements of the query. To test this, we evaluate ChatGPT's performance on a large sample of two reading comprehension datasets under both open-book and closed-book settings, varying the repetition of each question to 1, 3, or 5 times per prompt. Our findings indicate that the model does not demonstrate sensitivity to repeated questions, highlighting its robustness and consistency in this context.

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1