This paper shows that large language models struggle with commonsense reasoning due to a bias towards explicit conditions, which can be misled by irrelevant information, and that this issue can be improved by adjusting the task framing or using lightweight prompting. Practitioners caring about the reliability of language models in real-world applications might want to consider this when using them for tasks that require critical thinking.
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