Apple researchers found significant flaws in the reasoning skills of large language models from various developers. The study showed that even small changes in question wording could drastically alter the models' answers, raising concerns about their reliability. This inconsistency highlights the models' dependence on recognizing patterns instead of using true logical reasoning. Adding irrelevant details to questions further exposed this weakness, causing the models to provide wildly different answers.
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